| 2024 | 23 Da Yan, Ahmed Abdeen Hamed, Jake Y. Chen, Mohammed J. Zaki |
| 2024 | 2nd Workshop on Causal Inference and Machine Learning in Practice. Jeong-Yoon Lee, Yifeng Wu, Totte Harinen, Jing Pan, Paul Lo, Zhenyu Zhao, Huigang Chen, Zeyu Zheng, Hasta Vanchinathan, Yingfei Wang, Roland Stevenson |
| 2024 | 3rd Workshop on End-End Customer Journey Optimization. Shadow Zhao, Mert Bay, Anbang Xu, Neha Gupta |
| 2024 | 3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). Chen Zhao, Feng Chen, Xintao Wu, Jundong Li, Haifeng Chen |
| 2024 | 3rd Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM). Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Wei Hua, Haifeng Chen |
| 2024 | A Deep Prediction Framework for Multi-Source Information via Heterogeneous GNN. Zhen Wu, Jingya Zhou, Jinghui Zhang, Ling Liu, Chizhou Huang |
| 2024 | A Fast Exact Algorithm to Enumerate Maximal Pseudo-cliques in Large Sparse Graphs. Ahsanur Rahman, Kalyan Roy, Ramiza Maliha, Townim Faisal Chowdhury |
| 2024 | A Hands-on Introduction to Time Series Classification and Regression. Anthony J. Bagnall, Matthew Middlehurst, Germain Forestier, Ali Ismail-Fawaz, Antoine Guillaume, David Guijo-Rubio, Chang Wei Tan, Angus Dempster, Geoffrey I. Webb |
| 2024 | A Hierarchical Context Augmentation Method to Improve Retrieval-Augmented LLMs on Scientific Papers. Tian-Yi Che, Xian-Ling Mao, Tian Lan, Heyan Huang |
| 2024 | A Hierarchical and Disentangling Interest Learning Framework for Unbiased and True News Recommendation. Shoujin Wang, Wentao Wang, Xiuzhen Zhang, Yan Wang, Huan Liu, Fang Chen |
| 2024 | A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs. Amitoz Azad, Yuan Fang |
| 2024 | A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist. Wentao Zhang, Lingxuan Zhao, Haochong Xia, Shuo Sun, Jiaze Sun, Molei Qin, Xinyi Li, Yuqing Zhao, Yilei Zhao, Xinyu Cai, Longtao Zheng, Xinrun Wang, Bo An |
| 2024 | A Novel Feature Space Augmentation Method to Improve Classification Performance and Evaluation Reliability. Sakhawat Hossain Saimon, Tanzira Najnin, Jianhua Ruan |
| 2024 | A Novel Prompt Tuning for Graph Transformers: Tailoring Prompts to Graph Topologies. Jingchao Wang, Zhengnan Deng, Tongxu Lin, Wenyuan Li, Shaobin Ling |
| 2024 | A Population-to-individual Tuning Framework for Adapting Pretrained LM to On-device User Intent Prediction. Jiahui Gong, Jingtao Ding, Fanjin Meng, Guilong Chen, Hong Chen, Shen Zhao, Haisheng Lu, Yong Li |
| 2024 | A Review of Graph Neural Networks in Epidemic Modeling. Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin |
| 2024 | A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano |
| 2024 | A Self-boosted Framework for Calibrated Ranking. Shunyu Zhang, Hu Liu, Wentian Bao, Enyun Yu, Yang Song |
| 2024 | A Survey of Large Language Models for Graphs. Xubin Ren, Jiabin Tang, Dawei Yin, Nitesh V. Chawla, Chao Huang |
| 2024 | A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin |
| 2024 | A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models. Wenqi Fan, Yujuan Ding, Liangbo Ning, Shijie Wang, Hengyun Li, Dawei Yin, Tat-Seng Chua, Qing Li |
| 2024 | A Survey on Safe Multi-Modal Learning Systems. Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng |
| 2024 | A Tutorial on Multi-Armed Bandit Applications for Large Language Models. Djallel Bouneffouf, Raphaël Féraud |
| 2024 | A Unified Core Structure in Multiplex Networks: From Finding the Densest Subgraph to Modeling User Engagement. Farnoosh Hashemi, Ali Behrouz |
| 2024 | A Uniformly Bounded Correlation Function for Spatial Point Patterns. Evgenia Martynova, Johannes Textor |
| 2024 | ACER: Accelerating Complex Event Recognition via Two-Phase Filtering under Range Bitmap-Based Indexes. Shizhe Liu, Haipeng Dai, Shaoxu Song, Meng Li, Jingsong Dai, Rong Gu, Guihai Chen |
| 2024 | ADSNet: Cross-Domain LTV Prediction with an Adaptive Siamese Network in Advertising. Ruize Wang, Hui Xu, Ying Cheng, Qi He, Xing Zhou, Rui Feng, Wei Xu, Lei Huang, Jie Jiang |
| 2024 | AGS-GNN: Attribute-guided Sampling for Graph Neural Networks. Siddhartha Shankar Das, S. M. Ferdous, Mahantesh M. Halappanavar, Edoardo Serra, Alex Pothen |
| 2024 | AI for Education (AI4EDU): Advancing Personalized Education with LLM and Adaptive Learning. Qingsong Wen, Jing Liang, Carles Sierra, Rose Luckin, Richard Jiarui Tong, Zitao Liu, Peng Cui, Jiliang Tang |
| 2024 | AI for Nature: From Science to Impact. Tanya Y. Berger-Wolf |
| 2024 | AIM: Attributing, Interpreting, Mitigating Data Unfairness. Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik F. Hamann, Hanghang Tong |
| 2024 | Achieving a Better Tradeoff in Multi-stage Recommender Systems through Personalization. Ariel Evnine, Stratis Ioannidis, Dimitris Kalimeris, Shankar Kalyanaraman, Weiwei Li, Israel Nir, Wei Sun, Udi Weinsberg |
| 2024 | AdKDD 2024. Abraham Bagherjeiran, Nemanja Djuric, Kuang-Chih Lee, Linsey Pang, Vladan Radosavljevic, Suju Rajan |
| 2024 | AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation. Weigang Lu, Ziyu Guan, Wei Zhao, Yaming Yang |
| 2024 | AdaRD: An Adaptive Response Denoising Framework for Robust Learner Modeling. Fangzhou Yao, Qi Liu, Linan Yue, Weibo Gao, Jiatong Li, Xin Li, Yuanjing He |
| 2024 | Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning. Xiao Han, Chen Zhu, Xiao Hu, Chuan Qin, Xiangyu Zhao, Hengshu Zhu |
| 2024 | Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization. Sheo Yon Jhin, Seojin Kim, Noseong Park |
| 2024 | Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma |
| 2024 | Ads Recommendation in a Collapsed and Entangled World. Junwei Pan, Wei Xue, Ximei Wang, Haibin Yu, Xun Liu, Shijie Quan, Xueming Qiu, Dapeng Liu, Lei Xiao, Jie Jiang |
| 2024 | Advances in Human Event Modeling: From Graph Neural Networks to Language Models. Songgaojun Deng, Maarten de Rijke, Yue Ning |
| 2024 | Advancing Molecule Invariant Representation via Privileged Substructure Identification. Ruijia Wang, Haoran Dai, Cheng Yang, Le Song, Chuan Shi |
| 2024 | Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously. Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen |
| 2024 | All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining. Haihong Zhao, Aochuan Chen, Xiangguo Sun, Hong Cheng, Jia Li |
| 2024 | An Efficient Local Search Algorithm for Large GD Advertising Inventory Allocation with Multilinear Constraints. Xiang He, Wuyang Mao, Zhenghang Xu, Yuanzhe Gu, Yundu Huang, Zhonglin Zu, Liang Wang, Mengyu Zhao, Mengchuan Zou |
| 2024 | An Efficient Subgraph GNN with Provable Substructure Counting Power. Zuoyu Yan, Junru Zhou, Liangcai Gao, Zhi Tang, Muhan Zhang |
| 2024 | An Energy-centric Framework for Category-free Out-of-distribution Node Detection in Graphs. Zheng Gong, Ying Sun |
| 2024 | An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems. Taeyoung Yun, Kanghoon Lee, Sujin Yun, Ilmyung Kim, Won-Woo Jung, Min-Cheol Kwon, Kyujin Choi, Yoohyeon Lee, Jinkyoo Park |
| 2024 | An Open and Large-Scale Dataset for Multi-Modal Climate Change-aware Crop Yield Predictions. Fudong Lin, Kaleb Guillot, Summer Crawford, Yihe Zhang, Xu Yuan, Nian-Feng Tzeng |
| 2024 | An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem. Huaiyuan Liu, Xianzhang Liu, Donghua Yang, Hongzhi Wang, Yingchi Long, Mengtong Ji, Dongjing Miao, Zhiyu Liang |
| 2024 | AnyLoss: Transforming Classification Metrics into Loss Functions. Do Heon Han, Nuno Moniz, Nitesh V. Chawla |
| 2024 | Approximate Matrix Multiplication over Sliding Windows. Ziqi Yao, Lianzhi Li, Mingsong Chen, Xian Wei, Cheng Chen |
| 2024 | Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization. Andrea Agiollo, Young In Kim, Rajiv Khanna |
| 2024 | Artificial Intelligence and Data Science for Healthcare: Bridging Data-Centric AI and People-Centric Healthcare. Shenda Hong, Daoxin Yin, Gongzheng Tang, Tianfan Fu, Liantao Ma, Junyi Gao, Mengling Feng, Mai Wang, Yu Yang, Fei Wang, Hongfang Liu, Luxia Zhang |
| 2024 | Asymmetric Beta Loss for Evidence-Based Safe Semi-Supervised Multi-Label Learning. Hao-Zhe Liu, Ming-Kun Xie, Chen-Chen Zong, Sheng-Jun Huang |
| 2024 | AsyncET: Asynchronous Representation Learning for Knowledge Graph Entity Typing. Yun-Cheng Wang, Xiou Ge, Bin Wang, C.-C. Jay Kuo |
| 2024 | Asynchronous Vertical Federated Learning for Kernelized AUC Maximization. Ke Zhang, Ganyu Wang, Han Li, Yulong Wang, Hong Chen, Bin Gu |
| 2024 | Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Leman Go Indifferent. Lorenz Kummer, Samir Moustafa, Sebastian Schrittwieser, Wilfried N. Gansterer, Nils M. Kriege |
| 2024 | Auctions with LLM Summaries. Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang |
| 2024 | AutoWebGLM: A Large Language Model-based Web Navigating Agent. Hanyu Lai, Xiao Liu, Iat Long Iong, Shuntian Yao, Yuxuan Chen, Pengbo Shen, Hao Yu, Hanchen Zhang, Xiaohan Zhang, Yuxiao Dong, Jie Tang |
| 2024 | AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting. Raphael Fischer, Amal Saadallah |
| 2024 | Automated Mining of Structured Knowledge from Text in the Era of Large Language Models. Yunyi Zhang, Ming Zhong, Siru Ouyang, Yizhu Jiao, Sizhe Zhou, Linyi Ding, Jiawei Han |
| 2024 | Automatic Multi-Task Learning Framework with Neural Architecture Search in Recommendations. Shen Jiang, Guanghui Zhu, Yue Wang, Chunfeng Yuan, Yihua Huang |
| 2024 | BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization. Zhongyi Pei, Zhiyao Cen, Yipeng Huang, Chen Wang, Lin Liu, Philip S. Yu, Mingsheng Long, Jianmin Wang |
| 2024 | BacktrackSTL: Ultra-Fast Online Seasonal-Trend Decomposition with Backtrack Technique. Haoyu Wang, Hongke Guo, Zhaoliang Zhu, You Zhang, Yu Zhou, Xudong Zheng |
| 2024 | Balanced Confidence Calibration for Graph Neural Networks. Hao Yang, Min Wang, Qi Wang, Mingrui Lao, Yun Zhou |
| 2024 | Beimingwu: A Learnware Dock System. Zhi-Hao Tan, Jian-Dong Liu, Xiao-Dong Bi, Peng Tan, Qin-Cheng Zheng, Hai-Tian Liu, Yi Xie, Xiao-Chuan Zou, Yang Yu, Zhi-Hua Zhou |
| 2024 | Beyond Binary Preference: Leveraging Bayesian Approaches for Joint Optimization of Ranking and Calibration. Chang Liu, QiWei Wang, Wenqing Lin, Yue Ding, Hongtao Lu |
| 2024 | Bi-Objective Contract Allocation for Guaranteed Delivery Advertising. Yan Li, Yundu Huang, Wuyang Mao, Furong Ye, Xiang He, Zhonglin Zu, Shaowei Cai |
| 2024 | Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era. Sunhao Dai, Chen Xu, Shicheng Xu, Liang Pang, Zhenhua Dong, Jun Xu |
| 2024 | Binder: Hierarchical Concept Representation through Order Embedding of Binary Vectors. Croix Gyurek, Niloy Talukder, Mohammad Al Hasan |
| 2024 | BitLINK: Temporal Linkage of Address Clusters in Bitcoin Blockchain. Sheng Zhong, Abdullah Mueen |
| 2024 | Bivariate Decision Trees: Smaller, Interpretable, More Accurate. Rasul Kairgeldin, Miguel Á. Carreira-Perpiñán |
| 2024 | BoKA: Bayesian Optimization based Knowledge Amalgamation for Multi-unknown-domain Text Classification. Linzhu Yu, Huan Li, Ke Chen, Lidan Shou |
| 2024 | Brant-X: A Unified Physiological Signal Alignment Framework. Daoze Zhang, Zhizhang Yuan, Junru Chen, Kerui Chen, Yang Yang |
| 2024 | Breaking Barriers: A Hands-On Tutorial on AI-Enabled Accessibility to Social Media Content. Julio Villena, Rosa Català, Janine García, Concepción Polo, Yessika Labrador, Francisco del-Valle, Bhargav Ayyagari |
| 2024 | Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation. Xinyu Lin, Wenjie Wang, Yongqi Li, Fuli Feng, See-Kiong Ng, Tat-Seng Chua |
| 2024 | Bridging and Compressing Feature and Semantic Spaces for Robust Graph Neural Networks: An Information Theory Perspective. Luying Zhong, Renjie Lin, Jiayin Li, Shiping Wang, Zheyi Chen |
| 2024 | Bringing Multimodality to Amazon Visual Search System. Xinliang Zhu, Sheng-Wei Huang, Han Ding, Jinyu Yang, Kelvin Chen, Tao Zhou, Tal Neiman, Ouye Xie, Son Tran, Benjamin Z. Yao, Douglas Gray, Anuj Bindal, Arnab Dhua |
| 2024 | Budgeted Multi-Armed Bandits with Asymmetric Confidence Intervals. Marco Heyden, Vadim Arzamasov, Edouard Fouché, Klemens Böhm |
| 2024 | Business Policy Experiments using Fractional Factorial Designs: Consumer Retention on DoorDash. Yixin Tang, Yicong Lin, Navdeep S. Sahni |
| 2024 | CAFO: Feature-Centric Explanation on Time Series Classification. Jaeho Kim, Seok-Ju Hahn, Yoontae Hwang, Junghye Lee, Seulki Lee |
| 2024 | CASA: Clustered Federated Learning with Asynchronous Clients. Boyi Liu, Yiming Ma, Zimu Zhou, Yexuan Shi, Shuyuan Li, Yongxin Tong |
| 2024 | CASH via Optimal Diversity for Ensemble Learning. Pranav Poduval, Sanjay Kumar Patnala, Gaurav Oberoi, Nitish Srivasatava, Siddhartha Asthana |
| 2024 | CAT: Interpretable Concept-based Taylor Additive Models. Viet Duong, Qiong Wu, Zhengyi Zhou, Hongjue Zhao, Chenxiang Luo, Eric Zavesky, Huaxiu Yao, Huajie Shao |
| 2024 | CE-RCFR: Robust Counterfactual Regression for Consensus-Enabled Treatment Effect Estimation. Fan Wang, Chaochao Chen, Weiming Liu, Tianhao Fan, Xinting Liao, Yanchao Tan, Lianyong Qi, Xiaolin Zheng |
| 2024 | CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning. Ulrik Friis-Jensen, Frederik L. Johansen, Andy S. Anker, Erik B. Dam, Kirsten M. Ø. Jensen, Raghavendra Selvan |
| 2024 | COMET: NFT Price Prediction with Wallet Profiling. Tianfu Wang, Liwei Deng, Chao Wang, Jianxun Lian, Yue Yan, Nicholas Jing Yuan, Qi Zhang, Hui Xiong |
| 2024 | CONFIDE: Contextual Finite Difference Modelling of PDEs. Ori Linial, Orly Avner, Dotan Di Castro |
| 2024 | CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect. Jiehui Zhou, Linxiao Yang, Xingyu Liu, Xinyue Gu, Liang Sun, Wei Chen |
| 2024 | Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift. Mouxiang Chen, Lefei Shen, Han Fu, Zhuo Li, Jianling Sun, Chenghao Liu |
| 2024 | Can Modifying Data Address Graph Domain Adaptation? Renhong Huang, Jiarong Xu, Xin Jiang, Ruichuan An, Yang Yang |
| 2024 | Can a Deep Learning Model be a Jintai Chen, Jiahuan Yan, Qiyuan Chen, Danny Z. Chen, Jian Wu, Jimeng Sun |
| 2024 | Capturing Homogeneous Influence among Students: Hypergraph Cognitive Diagnosis for Intelligent Education Systems. Junhao Shen, Hong Qian, Shuo Liu, Wei Zhang, Bo Jiang, Aimin Zhou |
| 2024 | Causal Estimation of Exposure Shifts with Neural Networks and an Application to Inform Air Quality Standards in the US. Mauricio Tec, Kevin Josey, Oladimeji Mudele, Francesca Dominici |
| 2024 | Causal Inference with Latent Variables: Recent Advances and Future Prospectives. Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li |
| 2024 | Causal Machine Learning for Cost-Effective Allocation of Development Aid. Milan Kuzmanovic, Dennis Frauen, Tobias Hatt, Stefan Feuerriegel |
| 2024 | Causal Subgraph Learning for Generalizable Inductive Relation Prediction. Mei Li, Xiaoguang Liu, Hua Ji, Shuangjia Zheng |
| 2024 | Certified Robustness on Visual Graph Matching via Searching Optimal Smoothing Range. Huaqing Shao, Lanjun Wang, Yongwei Wang, Qibing Ren, Junchi Yan |
| 2024 | Chaining Text-to-Image and Large Language Model: A Novel Approach for Generating Personalized e-commerce Banners. Shanu Vashishtha, Abhinav Prakash, Lalitesh Morishetti, Kaushiki Nag, Yokila Arora, Sushant Kumar, Kannan Achan |
| 2024 | CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent. Liang-Bo Ning, Shijie Wang, Wenqi Fan, Qing Li, Xin Xu, Hao Chen, Feiran Huang |
| 2024 | Choosing a Proxy Metric from Past Experiments. Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour, Jacopo Soriano, Steve Yadlowsky |
| 2024 | Chromosomal Structural Abnormality Diagnosis by Homologous Similarity. Juren Li, Fanzhe Fu, Ran Wei, Yifei Sun, Zeyu Lai, Ning Song, Xin Chen, Yang Yang |
| 2024 | Class-incremental Learning for Time Series: Benchmark and Evaluation. Zhongzheng Qiao, Quang Pham, Zhen Cao, Hoang H. Le, Ponnuthurai N. Suganthan, Xudong Jiang, Savitha Ramasamy |
| 2024 | Cluster-Wide Task Slowdown Detection in Cloud System. Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng |
| 2024 | Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction. Ke Cheng, Linzhi Peng, Junchen Ye, Leilei Sun, Bowen Du |
| 2024 | CoLiDR: Concept Learning using Aggregated Disentangled Representations. Sanchit Sinha, Guangzhi Xiong, Aidong Zhang |
| 2024 | CoMAL: Contrastive Active Learning for Multi-Label Text Classification. Cheng Peng, Haobo Wang, Ke Chen, Lidan Shou, Chang Yao, Runze Wu, Gang Chen |
| 2024 | CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation. Junda Wu, Cheng-Chun Chang, Tong Yu, Zhankui He, Jianing Wang, Yupeng Hou, Julian J. McAuley |
| 2024 | CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control. Jingqing Ruan, Ziyue Li, Hua Wei, Haoyuan Jiang, Jiaming Lu, Xuantang Xiong, Hangyu Mao, Rui Zhao |
| 2024 | Communication-efficient Multi-service Mobile Traffic Prediction by Leveraging Cross-service Correlations. Zhiying Feng, Qiong Wu, Xu Chen |
| 2024 | Compact Decomposition of Irregular Tensors for Data Compression: From Sparse to Dense to High-Order Tensors. Taehyung Kwon, Jihoon Ko, Jinhong Jung, Jun-Gi Jang, Kijung Shin |
| 2024 | CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification. Lele Cao, Vilhelm von Ehrenheim, Mark Granroth-Wilding, Richard Anselmo Stahl, Andrew McCornack, Armin Catovic, Dhiana Deva Cavalcanti Rocha |
| 2024 | Conditional Logical Message Passing Transformer for Complex Query Answering. Chongzhi Zhang, Zhiping Peng, Junhao Zheng, Qianli Ma |
| 2024 | Conformal Counterfactual Inference under Hidden Confounding. Zonghao Chen, Ruocheng Guo, Jean-Francois Ton, Yang Liu |
| 2024 | Conformalized Link Prediction on Graph Neural Networks. Tianyi Zhao, Jian Kang, Lu Cheng |
| 2024 | Consistency and Discrepancy-Based Contrastive Tripartite Graph Learning for Recommendations. Linxin Guo, Yaochen Zhu, Min Gao, Yinghui Tao, Junliang Yu, Chen Chen |
| 2024 | Contextual Distillation Model for Diversified Recommendation. Fan Li, Xu Si, Shisong Tang, Dingmin Wang, Kunyan Han, Bing Han, Guorui Zhou, Yang Song, Hechang Chen |
| 2024 | Continual Collaborative Distillation for Recommender System. Gyuseok Lee, SeongKu Kang, Wonbin Kweon, Hwanjo Yu |
| 2024 | ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model. Yuanshao Zhu, James Jian Qiao Yu, Xiangyu Zhao, Qidong Liu, Yongchao Ye, Wei Chen, Zijian Zhang, Xuetao Wei, Yuxuan Liang |
| 2024 | Controllable Multi-Behavior Recommendation for In-Game Skins with Large Sequential Model. Yanjie Gou, Yuanzhou Yao, Zhao Zhang, Yiqing Wu, Yi Hu, Fuzhen Zhuang, Jiangming Liu, Yongjun Xu |
| 2024 | Conversational Dueling Bandits in Generalized Linear Models. Shuhua Yang, Hui Yuan, Xiaoying Zhang, Mengdi Wang, Hong Zhang, Huazheng Wang |
| 2024 | Cost-Efficient Fraud Risk Optimization with Submodularity in Insurance Claim. Yupeng Wu, Zhibo Zhu, Chaoyi Ma, Hong Qian, Xingyu Lu, Yangwenhui Zhang, Xiaobo Qin, Binjie Fei, Jun Zhou, Aimin Zhou |
| 2024 | Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time. Haiyuan Zhao, Guohao Cai, Jieming Zhu, Zhenhua Dong, Jun Xu, Ji-Rong Wen |
| 2024 | Counterfactual Generative Models for Time-Varying Treatments. Shenghao Wu, Wenbin Zhou, Minshuo Chen, Shixiang Zhu |
| 2024 | Cross-Context Backdoor Attacks against Graph Prompt Learning. Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor W. Tsang, Xiangliang Zhang |
| 2024 | Cross-Domain LifeLong Sequential Modeling for Online Click-Through Rate Prediction. Ruijie Hou, Zhaoyang Yang, Ming Yu, Hongyu Lu, Zhuobin Zheng, Yu Chen, Qinsong Zeng, Ming Chen |
| 2024 | CrossLight: Offline-to-Online Reinforcement Learning for Cross-City Traffic Signal Control. Qian Sun, Rui Zha, Le Zhang, Jingbo Zhou, Yu Mei, Zhiling Li, Hui Xiong |
| 2024 | Customizing Graph Neural Network for CAD Assembly Recommendation. Fengqi Liang, Huan Zhao, Yuhan Quan, Wei Fang, Chuan Shi |
| 2024 | CutAddPaste: Time Series Anomaly Detection by Exploiting Abnormal Knowledge. Rui Wang, Xudong Mou, Renyu Yang, Kai Gao, Pin Liu, Chongwei Liu, Tianyu Wo, Xudong Liu |
| 2024 | DAG: Deep Adaptive and Generative Chang Liu, Yuwen Yang, Yue Ding, Hongtao Lu, Wenqing Lin, Ziming Wu, Wendong Bi |
| 2024 | DARE to Diversify: DAta Driven and Diverse LLM REd Teaming. Manish Nagireddy, Bernat Guillen Pegueroles, Ioana Baldini |
| 2024 | DDCDR: A Disentangle-based Distillation Framework for Cross-Domain Recommendation. Zhicheng An, Zhexu Gu, Li Yu, Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Lihong Gu, Jinjie Gu |
| 2024 | DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback. Yiqing Wu, Ruobing Xie, Zhao Zhang, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Zhanhui Kang, Yongjun Xu |
| 2024 | DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation. Kairui Fu, Shengyu Zhang, Zheqi Lv, Jingyuan Chen, Jiwei Li |
| 2024 | DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization. Xin Sun, Liang Wang, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang |
| 2024 | DPHGNN: A Dual Perspective Hypergraph Neural Networks. Siddhant Saxena, Shounak Ghatak, Raghu Kolla, Debashis Mukherjee, Tanmoy Chakraborty |
| 2024 | DPSW-Sketch: A Differentially Private Sketch Framework for Frequency Estimation over Sliding Windows. Yiping Wang, Yanhao Wang, Cen Chen |
| 2024 | DUE: Dynamic Uncertainty-Aware Explanation Supervision via 3D Imputation. Qilong Zhao, Yifei Zhang, Mengdan Zhu, Siyi Gu, Yuyang Gao, Xiaofeng Yang, Liang Zhao |
| 2024 | Dataset Condensation for Time Series Classification via Dual Domain Matching. Zhanyu Liu, Ke Hao, Guanjie Zheng, Yanwei Yu |
| 2024 | Dataset Regeneration for Sequential Recommendation. Mingjia Yin, Hao Wang, Wei Guo, Yong Liu, Suojuan Zhang, Sirui Zhao, Defu Lian, Enhong Chen |
| 2024 | Debiased Recommendation with Noisy Feedback. Haoxuan Li, Chunyuan Zheng, Wenjie Wang, Hao Wang, Fuli Feng, Xiao-Hua Zhou |
| 2024 | Decision Focused Causal Learning for Direct Counterfactual Marketing Optimization. Hao Zhou, Rongxiao Huang, Shaoming Li, Guibin Jiang, Jiaqi Zheng, Bing Cheng, Wei Lin |
| 2024 | Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text. Sara Abdali, Richard Anarfi, C. J. Barberan, Jia He |
| 2024 | Decomposed Attention Segment Recurrent Neural Network for Orbit Prediction. Seungwon Jeong, Soyeon Woo, Daewon Chung, Simon S. Woo, Youjin Shin |
| 2024 | Deep Bag-of-Words Model: An Efficient and Interpretable Relevance Architecture for Chinese E-Commerce. Zhe Lin, Jiwei Tan, Dan Ou, Xi Chen, Shaowei Yao, Bo Zheng |
| 2024 | Deep Ensemble Shape Calibration: Multi-Field Post-hoc Calibration in Online Advertising. Shuai Yang, Hao Yang, Zhuang Zou, Linhe Xu, Shuo Yuan, Yifan Zeng |
| 2024 | Dense Subgraph Discovery Meets Strong Triadic Closure. Chamalee Wickrama Arachchi, Iiro Kumpulainen, Nikolaj Tatti |
| 2024 | Detecting Abnormal Operations in Concentrated Solar Power Plants from Irregular Sequences of Thermal Images. Sukanya Patra, Nicolas Sournac, Souhaib Ben Taieb |
| 2024 | Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns. Zheyuan Zhang, Zehong Wang, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye |
| 2024 | DiffCrime: A Multimodal Conditional Diffusion Model for Crime Risk Map Inference. Shuliang Wang, Xinyu Pan, Sijie Ruan, Haoyu Han, Ziyu Wang, Hanning Yuan, Jiabao Zhu, Qi Li |
| 2024 | Diffusion Model-based Mobile Traffic Generation with Open Data for Network Planning and Optimization. Haoye Chai, Tao Jiang, Li Yu |
| 2024 | Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations. Jing Long, Guanhua Ye, Tong Chen, Yang Wang, Meng Wang, Hongzhi Yin |
| 2024 | DiffusionE: Reasoning on Knowledge Graphs via Diffusion-based Graph Neural Networks. Zongsheng Cao, Jing Li, Zigan Wang, Jinliang Li |
| 2024 | DipDNN: Preserving Inverse Consistency and Approximation Efficiency for Invertible Learning. Jingyi Yuan, Yang Weng, Erik Blasch |
| 2024 | DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation. Kounianhua Du, Jizheng Chen, Jianghao Lin, Yunjia Xi, Hangyu Wang, Xinyi Dai, Bo Chen, Ruiming Tang, Weinan Zhang |
| 2024 | Disentangled Multi-interest Representation Learning for Sequential Recommendation. Yingpeng Du, Ziyan Wang, Zhu Sun, Yining Ma, Hongzhi Liu, Jie Zhang |
| 2024 | Distributed Harmonization: Federated Clustered Batch Effect Adjustment and Generalization. Bao Hoang, Yijiang Pang, Siqi Liang, Liang Zhan, Paul M. Thompson, Jiayu Zhou |
| 2024 | Distributed Thresholded Counting with Limited Interaction. Xiaoyi Zhu, Yuxiang Tian, Zengfeng Huang |
| 2024 | Distributional Network of Networks for Modeling Data Heterogeneity. Jun Wu, Jingrui He, Hanghang Tong |
| 2024 | Diverse Intra- and Inter-Domain Activity Style Fusion for Cross-Person Generalization in Activity Recognition. Junru Zhang, Lang Feng, Zhidan Liu, Yuhan Wu, Yang He, Yabo Dong, Duanqing Xu |
| 2024 | Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise. Kaize Ding, Xiaoxiao Ma, Yixin Liu, Shirui Pan |
| 2024 | Domain-Driven LLM Development: Insights into RAG and Fine-Tuning Practices. José Cassio dos Santos Junior, Rachel Hu, Richard Song, Yun-Fei Bai |
| 2024 | Double Correction Framework for Denoising Recommendation. Zhuangzhuang He, Yifan Wang, Yonghui Yang, Peijie Sun, Le Wu, Haoyue Bai, Jinqi Gong, Richang Hong, Min Zhang |
| 2024 | DuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation. Deguo Xia, Weiming Zhang, Xiyan Liu, Wei Zhang, Chenting Gong, Jizhou Huang, Mengmeng Yang, Diange Yang |
| 2024 | Dual-Assessment Driven Pruning: Iterative Optimizing Layer-wise Sparsity for Large Language Model. Qinghui Sun, Weilun Wang, Yanni Zhu, Shenghuan He, Hao Yi, Zehua Cai, Hong Liu |
| 2024 | DyGKT: Dynamic Graph Learning for Knowledge Tracing. Ke Cheng, Linzhi Peng, Pengyang Wang, Junchen Ye, Leilei Sun, Bowen Du |
| 2024 | DyPS: Dynamic Parameter Sharing in Multi-Agent Reinforcement Learning for Spatio-Temporal Resource Allocation. Jingwei Wang, Qianyue Hao, Wenzhen Huang, Xiaochen Fan, Zhentao Tang, Bin Wang, Jianye Hao, Yong Li |
| 2024 | Dynamic Hotel Pricing at Online Travel Platforms: A Popularity and Competitiveness Aware Demand Learning Approach. Fanwei Zhu, Wendong Xiao, Yao Yu, Zemin Liu, Zulong Chen, Weibin Cai |
| 2024 | Dynamic Neural Dowker Network: Approximating Persistent Homology in Dynamic Directed Graphs. Hao Li, Hao Jiang, Jiajun Fan, Dongsheng Ye, Liang Du |
| 2024 | Dynamic Pricing for Multi-Retailer Delivery Platforms with Additive Deep Learning and Evolutionary Optimization. Ahmed Abdulaal, Ali Polat, Hari Narayan, Wenrong Zeng, Yimin Yi |
| 2024 | Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English. Xiao Zhang, Ruoyu Xiang, Chenhan Yuan, Duanyu Feng, Weiguang Han, Alejandro Lopez-Lira, Xiao-Yang Liu, Meikang Qiu, Sophia Ananiadou, Min Peng, Jimin Huang, Qianqian Xie |
| 2024 | EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration. Ye Wang, Jiahao Xun, Minjie Hong, Jieming Zhu, Tao Jin, Wang Lin, Haoyuan Li, Linjun Li, Yan Xia, Zhou Zhao, Zhenhua Dong |
| 2024 | EEG2Rep: Enhancing Self-supervised EEG Representation Through Informative Masked Inputs. Navid Mohammadi Foumani, Geoffrey Mackellar, Soheila Ghane, Saad Irtza, Nam Nguyen, Mahsa Salehi |
| 2024 | ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems. Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang |
| 2024 | EcoVal: An Efficient Data Valuation Framework for Machine Learning. Ayush K. Tarun, Vikram S. Chundawat, Murari Mandal, Hong Ming Tan, Bowei Chen, Mohan S. Kankanhalli |
| 2024 | Effective Clustering on Large Attributed Bipartite Graphs. Renchi Yang, Yidu Wu, Xiaoyang Lin, Qichen Wang, Tsz Nam Chan, Jieming Shi |
| 2024 | Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs. Hewen Wang, Renchi Yang, Xiaokui Xiao |
| 2024 | Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusion. Hao Zeng, Jiaqi Wang, Avirup Das, Junying He, Kunpeng Han, Haoyuan Hu, Mingfei Sun |
| 2024 | Efficient Decision Rule List Learning via Unified Sequence Submodular Optimization. Linxiao Yang, Jingbang Yang, Liang Sun |
| 2024 | Efficient Discovery of Time Series Motifs under both Length Differences and Warping. Makoto Imamura, Takaaki Nakamura |
| 2024 | Efficient Exploration of the Rashomon Set of Rule-Set Models. Martino Ciaperoni, Han Xiao, Aristides Gionis |
| 2024 | Efficient Mixture of Experts based on Large Language Models for Low-Resource Data Preprocessing. Mengyi Yan, Yaoshu Wang, Kehan Pang, Min Xie, Jianxin Li |
| 2024 | Efficient Topology-aware Data Augmentation for High-Degree Graph Neural Networks. Yurui Lai, Xiaoyang Lin, Renchi Yang, Hongtao Wang |
| 2024 | Efficient and Effective Anchored Densest Subgraph Search: A Convex-programming based Approach. Xiaowei Ye, Rong-Hua Li, Lei Liang, Zhizhen Liu, Longlong Lin, Guoren Wang |
| 2024 | Efficient and Effective Implicit Dynamic Graph Neural Network. Yongjian Zhong, Hieu Vu, Tianbao Yang, Bijaya Adhikari |
| 2024 | Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model. Jiang-Xin Shi, Chi Zhang, Tong Wei, Yufeng Li |
| 2024 | Embedding Two-View Knowledge Graphs with Class Inheritance and Structural Similarity. Kyuhwan Yeom, Hyeongjun Yang, Gayeon Park, Myeongheon Jeon, Yunjeong Ko, Byungkook Oh, Kyong-Ho Lee |
| 2024 | EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis. Zhiwei Liu, Kailai Yang, Qianqian Xie, Tianlin Zhang, Sophia Ananiadou |
| 2024 | Empower an End-to-end Scalable and Interpretable Data Science Ecosystem using Statistics, AI and Domain Science. Xihong Lin |
| 2024 | Enabling Collaborative Test-Time Adaptation in Dynamic Environment via Federated Learning. Jiayuan Zhang, Xuefeng Liu, Yukang Zhang, Guogang Zhu, Jianwei Niu, Shaojie Tang |
| 2024 | Enhancing Asymmetric Web Search through Question-Answer Generation and Ranking. Dezhi Ye, Jie Liu, Jiabin Fan, Bowen Tian, Tianhua Zhou, Xiang Chen, Jin Ma |
| 2024 | Enhancing Contrastive Learning on Graphs with Node Similarity. Hongliang Chi, Yao Ma |
| 2024 | Enhancing E-commerce Spelling Correction with Fine-Tuned Transformer Models. Arnab Dutta, Gleb Polushin, Xiaoshuang Zhang, Daniel Stein |
| 2024 | Enhancing Multi-field B2B Cloud Solution Matching via Contrastive Pre-training. Haonan Chen, Zhicheng Dou, Xuetong Hao, Yunhao Tao, Shiren Song, Zhenli Sheng |
| 2024 | Enhancing On-Device LLM Inference with Historical Cloud-Based LLM Interactions. Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lyu, Guihai Chen |
| 2024 | Enhancing Personalized Headline Generation via Offline Goal-conditioned Reinforcement Learning with Large Language Models. Xiaoyu Tan, Leijun Cheng, Xihe Qiu, Shaojie Shi, Yuan Cheng, Wei Chu, Yinghui Xu, Yuan Qi |
| 2024 | Enhancing Pre-Ranking Performance: Tackling Intermediary Challenges in Multi-Stage Cascading Recommendation Systems. Jianping Wei, Yujie Zhou, Zhengwei Wu, Ziqi Liu |
| 2024 | EntropyStop: Unsupervised Deep Outlier Detection with Loss Entropy. Yihong Huang, Yuang Zhang, Liping Wang, Fan Zhang, Xuemin Lin |
| 2024 | Equity, Diversity & Inclusion (EDI): Special Day at ACM KDD 2024. Tania Cerquitelli, Amin Mantrach |
| 2024 | Estimated Judge Reliabilities for Weighted Bradley-Terry-Luce Are Not Reliable. Andrew F. Dreher, Etienne Vouga, Donald S. Fussell |
| 2024 | European Data Science Day: KDD-2024 Special Day. Dunja Mladenic, Dumitru Roman |
| 2024 | Evading Community Detection via Counterfactual Neighborhood Search. Andrea Bernini, Fabrizio Silvestri, Gabriele Tolomei |
| 2024 | Expander Hierarchies for Normalized Cuts on Graphs. Kathrin Hanauer, Monika Henzinger, Robin Münk, Harald Räcke, Maximilian Vötsch |
| 2024 | Explainable Artificial Intelligence on Biosignals for Clinical Decision Support. Miriam Cindy Maurer, Jacqueline Michelle Metsch, Philip Hempel, Theresa Bender, Nicolai Spicher, Anne-Christin Hauschild |
| 2024 | Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay. Hussain Jagirdar, Rukma Talwadker, Aditya Pareek, Pulkit Agrawal, Tridib Mukherjee |
| 2024 | Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. Thomas Decker, Alexander Koebler, Michael Lebacher, Ingo Thon, Volker Tresp, Florian Buettner |
| 2024 | Explicit and Implicit Modeling via Dual-Path Transformer for Behavior Set-informed Sequential Recommendation. Ming Chen, Weike Pan, Zhong Ming |
| 2024 | Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval. Sachin Yadav, Deepak Saini, Anirudh Buvanesh, Bhawna Paliwal, Kunal Dahiya, Siddarth Asokan, Yashoteja Prabhu, Jian Jiao, Manik Varma |
| 2024 | FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML. Brian Liu, Rahul Mazumder |
| 2024 | FLAIM: AIM-based Synthetic Data Generation in the Federated Setting. Samuel Maddock, Graham Cormode, Carsten Maple |
| 2024 | FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation. Tong Xia, Abhirup Ghosh, Xinchi Qiu, Cecilia Mascolo |
| 2024 | FNSPID: A Comprehensive Financial News Dataset in Time Series. Zihan Dong, Xinyu Fan, Zhiyuan Peng |
| 2024 | FRNet: Frequency-based Rotation Network for Long-term Time Series Forecasting. Xinyu Zhang, Shanshan Feng, Jianghong Ma, Huiwei Lin, Xutao Li, Yunming Ye, Fan Li, Yew Soon Ong |
| 2024 | FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks. Renqiang Luo, Huafei Huang, Shuo Yu, Zhuoyang Han, Estrid He, Xiuzhen Zhang, Feng Xia |
| 2024 | Face4Rag: Factual Consistency Evaluation for Retrieval Augmented Generation in Chinese. Yunqi Xu, Tianchi Cai, Jiyan Jiang, Xierui Song |
| 2024 | Fair Column Subset Selection. Antonis Matakos, Bruno Ordozgoiti, Suhas Thejaswi |
| 2024 | FairMatch: Promoting Partial Label Learning by Unlabeled Samples. Jiahao Jiang, Yuheng Jia, Hui Liu, Junhui Hou |
| 2024 | Fairness in Streaming Submodular Maximization Subject to a Knapsack Constraint. Shuang Cui, Kai Han, Shaojie Tang, Feng Li, Jun Luo |
| 2024 | Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks. Jiaying Wu, Jiafeng Guo, Bryan Hooi |
| 2024 | False Positives in A/B Tests. Ron Kohavi, Nanyu Chen |
| 2024 | Fast Computation for the Forest Matrix of an Evolving Graph. Haoxin Sun, Xiaotian Zhou, Zhongzhi Zhang |
| 2024 | Fast Computation of Kemeny's Constant for Directed Graphs. Haisong Xia, Zhongzhi Zhang |
| 2024 | Fast Multidimensional Partial Fourier Transform with Automatic Hyperparameter Selection. Yong-chan Park, Jongjin Kim, U Kang |
| 2024 | Fast Query of Biharmonic Distance in Networks. Changan Liu, Ahad N. Zehmakan, Zhongzhi Zhang |
| 2024 | Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. Xueying Ding, Yue Zhao, Leman Akoglu |
| 2024 | Fast and Accurate Domain Adaptation for Irregular Tensor Decomposition. Junghun Kim, Ka Hyun Park, Jun-Gi Jang, U Kang |
| 2024 | FaultInsight: Interpreting Hyperscale Data Center Host Faults. Tingzhu Bi, Yang Zhang, Yicheng Pan, Yu Zhang, Meng Ma, Xinrui Jiang, Linlin Han, Feng Wang, Xian Liu, Ping Wang |
| 2024 | FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model. Feijie Wu, Zitao Li, Yaliang Li, Bolin Ding, Jing Gao |
| 2024 | FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction. Linghua Yang, Wantong Chen, Xiaoxi He, Shuyue Wei, Yi Xu, Zimu Zhou, Yongxin Tong |
| 2024 | FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics. Junyuan Hong, Carl Yang, Zhuangdi Zhu, Zheng Xu, Nathalie Baracaldo, Neil Shah, Salman Avestimehr, Jiayu Zhou |
| 2024 | FedNLR: Federated Learning with Neuron-wise Learning Rates. Haozhao Wang, Peirong Zheng, Xingshuo Han, Wenchao Xu, Ruixuan Li, Tianwei Zhang |
| 2024 | FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation. Gang Yan, Hao Wang, Xu Yuan, Jian Li |
| 2024 | FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning. Zihui Wang, Zheng Wang, Lingjuan Lyu, Zhaopeng Peng, Zhicheng Yang, Chenglu Wen, Rongshan Yu, Cheng Wang, Xiaoliang Fan |
| 2024 | FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs. Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, Wenxuan Wu, Chulin Xie, Yuhang Yao, Kai Zhang, Qifan Zhang, Yuhui Zhang, Carlee Joe-Wong, Salman Avestimehr, Chaoyang He |
| 2024 | Federated Graph Learning with Structure Proxy Alignment. Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li |
| 2024 | FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning. Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou |
| 2024 | First Workshop on Generative AI for Recommender Systems and Personalization. Narges Tabari, Aniket Anand Deshmukh, Wang-Cheng Kang, Hamed Zamani, Rashmi Gangadharaiah, Julian J. McAuley, George Karypis |
| 2024 | FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction. Muhao Xu, Zhenfeng Zhu, Youru Li, Shuai Zheng, Yawei Zhao, Kunlun He, Yao Zhao |
| 2024 | Flexible Graph Neural Diffusion with Latent Class Representation Learning. Liangtian Wan, Huijin Han, Lu Sun, Zixun Zhang, Zhaolong Ning, Xiaoran Yan, Feng Xia |
| 2024 | FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering. Tianchi Cai, Zhiwen Tan, Xierui Song, Tao Sun, Jiyan Jiang, Yunqi Xu, Yinger Zhang, Jinjie Gu |
| 2024 | Foundation Models for Time Series Analysis: A Tutorial and Survey. Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen |
| 2024 | Fragile Earth: Generative and Foundational Models for Sustainable Development. Emre Eftelioglu, Bistra Dilkina, Naoki Abe, Ramakrishnan Kannan, Yuzhou Chen, Yulia R. Gel, Kathleen Buckingham, Auroop R. Ganguly, James Hodson, Jiafu Mao |
| 2024 | FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition. Jihyeong Jeon, Jiwon Park, Chanhee Park, U Kang |
| 2024 | Fredformer: Frequency Debiased Transformer for Time Series Forecasting. Xihao Piao, Zheng Chen, Taichi Murayama, Yasuko Matsubara, Yasushi Sakurai |
| 2024 | From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models. Xumeng Wen, Han Zhang, Shun Zheng, Wei Xu, Jiang Bian |
| 2024 | From Variability to Stability: Advancing RecSys Benchmarking Practices. Valeriy Shevchenko, Nikita Belousov, Alexey Vasilev, Vladimir Zholobov, Artyom Sosedka, Natalia Semenova, Anna Volodkevich, Andrey V. Savchenko, Alexey Zaytsev |
| 2024 | From Word-prediction to Complex Skills: Compositional Thinking and Metacognition in LLMs. Sanjeev Arora |
| 2024 | FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin |
| 2024 | Future Impact Decomposition in Request-level Recommendations. Xiaobei Wang, Shuchang Liu, Xueliang Wang, Qingpeng Cai, Lantao Hu, Han Li, Peng Jiang, Kun Gai, Guangming Xie |
| 2024 | GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models. Yi Fang, Dongzhe Fan, Daochen Zha, Qiaoyu Tan |
| 2024 | GEO: Generative Engine Optimization. Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande |
| 2024 | GPFedRec: Graph-Guided Personalization for Federated Recommendation. Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang |
| 2024 | GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security. Xuanqing Liu, Runhui Wang, Yang Song, Luyang Kong |
| 2024 | GRILLBot In Practice: Lessons and Tradeoffs Deploying Large Language Models for Adaptable Conversational Task Assistants. Sophie Fischer, Carlos Gemmell, Niklas Tecklenburg, Iain Mackie, Federico Rossetto, Jeffrey Dalton |
| 2024 | Gandalf: Learning Label-label Correlations in Extreme Multi-label Classification via Label Features. Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar |
| 2024 | Generative AI Day. Jie Tang, Yuxiao Dong, Michalis Vazirgiannis |
| 2024 | Generative AI in E-Commerce: What Can We Expect? Haixun Wang |
| 2024 | Generative Auto-bidding via Conditional Diffusion Modeling. Jiayan Guo, Yusen Huo, Zhilin Zhang, Tianyu Wang, Chuan Yu, Jian Xu, Bo Zheng, Yan Zhang |
| 2024 | Generative Pretrained Hierarchical Transformer for Time Series Forecasting. Zhiding Liu, Jiqian Yang, Mingyue Cheng, Yucong Luo, Zhi Li |
| 2024 | GeoMix: Towards Geometry-Aware Data Augmentation. Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan |
| 2024 | Geometric View of Soft Decorrelation in Self-Supervised Learning. Yifei Zhang, Hao Zhu, Zixing Song, Yankai Chen, Xinyu Fu, Ziqiao Meng, Piotr Koniusz, Irwin King |
| 2024 | GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing. Chengqing Yu, Fei Wang, Zezhi Shao, Tangwen Qian, Zhao Zhang, Wei Wei, Yongjun Xu |
| 2024 | Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement Learning. Danqing Wang, Antonis Antoniades, Kha-Dinh Luong, Edwin Zhang, Mert Kosan, Jiachen Li, Ambuj K. Singh, William Yang Wang, Lei Li |
| 2024 | Going Where, by Whom, and at What Time: Next Location Prediction Considering User Preference and Temporal Regularity. Tianao Sun, Ke Fu, Weiming Huang, Kai Zhao, Yongshun Gong, Meng Chen |
| 2024 | GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan |
| 2024 | GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting. Yimeng Bai, Yang Zhang, Fuli Feng, Jing Lu, Xiaoxue Zang, Chenyi Lei, Yang Song |
| 2024 | Graph Anomaly Detection with Few Labels: A Data-Centric Approach. Xiaoxiao Ma, Ruikun Li, Fanzhen Liu, Kaize Ding, Jian Yang, Jia Wu |
| 2024 | Graph Bottlenecked Social Recommendation. Yonghui Yang, Le Wu, Zihan Wang, Zhuangzhuang He, Richang Hong, Meng Wang |
| 2024 | Graph Condensation for Open-World Graph Learning. Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin |
| 2024 | Graph Cross Supervised Learning via Generalized Knowledge. Xiangchi Yuan, Yijun Tian, Chunhui Zhang, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang |
| 2024 | Graph Data Condensation via Self-expressive Graph Structure Reconstruction. Zhanyu Liu, Chaolv Zeng, Guanjie Zheng |
| 2024 | Graph Intelligence with Large Language Models and Prompt Learning. Jia Li, Xiangguo Sun, Yuhan Li, Zhixun Li, Hong Cheng, Jeffrey Xu Yu |
| 2024 | Graph Machine Learning Meets Multi-Table Relational Data. Quan Gan, Minjie Wang, David Wipf, Christos Faloutsos |
| 2024 | Graph Mamba: Towards Learning on Graphs with State Space Models. Ali Behrouz, Farnoosh Hashemi |
| 2024 | Graph Reasoning with LLMs (GReaL). Anton Tsitsulin, Bryan Perozzi, Bahare Fatemi, Jonathan J. Halcrow |
| 2024 | GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications. Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis |
| 2024 | GraphWiz: An Instruction-Following Language Model for Graph Computational Problems. Nuo Chen, Yuhan Li, Jianheng Tang, Jia Li |
| 2024 | Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey). Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly |
| 2024 | Handling Varied Objectives by Online Decision Making. Lanjihong Ma, Zhen-Yu Zhang, Yao-Xiang Ding, Zhi-Hua Zhou |
| 2024 | Harm Mitigation in Recommender Systems under User Preference Dynamics. Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis |
| 2024 | Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments. Yile Liang, Jiuxia Zhao, Donghui Li, Jie Feng, Chen Zhang, Xuetao Ding, Jinghua Hao, Renqing He |
| 2024 | Hate Speech Detection with Generalizable Target-aware Fairness. Tong Chen, Danny Wang, Xurong Liang, Marten Risius, Gianluca Demartini, Hongzhi Yin |
| 2024 | Health Day: Building Health AI Ecosystem: From Data Harmonization to Knowledge Discovery. Jake Y. Chen, Peipei Ping |
| 2024 | Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting. Zheng Dong, Renhe Jiang, Haotian Gao, Hangchen Liu, Jinliang Deng, Qingsong Wen, Xuan Song |
| 2024 | Heterogeneous Contrastive Learning for Foundation Models and Beyond. Lecheng Zheng, Baoyu Jing, Zihao Li, Hanghang Tong, Jingrui He |
| 2024 | Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction. Juzheng Zhang, Lanning Wei, Zhen Xu, Quanming Yao |
| 2024 | HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning. Zhuoning Guo, Duanyi Yao, Qiang Yang, Hao Liu |
| 2024 | HiGPT: Heterogeneous Graph Language Model. Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Long Xia, Dawei Yin, Chao Huang |
| 2024 | Hierarchical Knowledge Guided Fault Intensity Diagnosis of Complex Industrial Systems. Yu Sha, Shuiping Gou, Bo Liu, Johannes Faber, Ningtao Liu, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou |
| 2024 | Hierarchical Linear Symbolized Tree-Structured Neural Processes. Jinyang Tai, Yi-Ke Guo |
| 2024 | Hierarchical Neural Constructive Solver for Real-world TSP Scenarios. Yong Liang Goh, Zhiguang Cao, Yining Ma, Yanfei Dong, Mohammed Haroon Dupty, Wee Sun Lee |
| 2024 | High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates. Fred Lu, Ryan R. Curtin, Edward Raff, Francis Ferraro, James Holt |
| 2024 | How Powerful is Graph Filtering for Recommendation. Shaowen Peng, Xin Liu, Kazunari Sugiyama, Tsunenori Mine |
| 2024 | How to Avoid Jumping to Conclusions: Measuring the Robustness of Outstanding Facts in Knowledge Graphs. Hanhua Xiao, Yuchen Li, Yanhao Wang, Panagiotis Karras, Kyriakos Mouratidis, Natalia Rozalia Avlona |
| 2024 | Hyper-Local Deformable Transformers for Text Spotting on Historical Maps. Yijun Lin, Yao-Yi Chiang |
| 2024 | Hypformer: Exploring Efficient Transformer Fully in Hyperbolic Space. Menglin Yang, Harshit Verma, Delvin Ce Zhang, Jiahong Liu, Irwin King, Rex Ying |
| 2024 | IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li |
| 2024 | ITPNet: Towards Instantaneous Trajectory Prediction for Autonomous Driving. Rongqing Li, Changsheng Li, Yuhang Li, Hanjie Li, Yi Chen, Ye Yuan, Guoren Wang |
| 2024 | Image Similarity Using an Ensemble of Context-Sensitive Models. Zukang Liao, Min Chen |
| 2024 | Improved Active Covering via Density-Based Space Transformation. MohammadHossein Bateni, Hossein Esfandiari, Samira Hossein Ghorban, Alipasha Montaseri |
| 2024 | Improving Ego-Cluster for Network Effect Measurement. Wentao Su, Weitao Duan |
| 2024 | Improving Multi-modal Recommender Systems by Denoising and Aligning Multi-modal Content and User Feedback. Guipeng Xv, Xinyu Li, Ruobing Xie, Chen Lin, Chong Liu, Feng Xia, Zhanhui Kang, Leyu Lin |
| 2024 | Improving Robustness of Hyperbolic Neural Networks by Lipschitz Analysis. Yuekang Li, Yidan Mao, Yifei Yang, Dongmian Zou |
| 2024 | Improving the Consistency in Cross-Lingual Cross-Modal Retrieval with 1-to-K Contrastive Learning. Zhijie Nie, Richong Zhang, Zhangchi Feng, Hailang Huang, Xudong Liu |
| 2024 | ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation. Tong Nie, Guoyang Qin, Wei Ma, Yuewen Mei, Jian Sun |
| 2024 | InLN: Knowledge-aware Incremental Leveling Network for Dynamic Advertising. Xujia Li, Jingshu Peng, Lei Chen |
| 2024 | Inductive Modeling for Realtime Cold Start Recommendations. Chandler Zuo, Jonathan Castaldo, Hanqing Zhu, Haoyu Zhang, Ji Liu, Yangpeng Ou, Xiao Kong |
| 2024 | Inference Optimization of Foundation Models on AI Accelerators. Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis |
| 2024 | Influence Maximization via Graph Neural Bandits. Yuting Feng, Vincent Y. F. Tan, Bogdan Cautis |
| 2024 | Integrating System State into Spatio Temporal Graph Neural Network for Microservice Workload Prediction. Yang Luo, Mohan Gao, Zhemeng Yu, Haoyuan Ge, Xiaofeng Gao, Tengwei Cai, Guihai Chen |
| 2024 | Intelligent Agents with LLM-based Process Automation. Yanchu Guan, Dong Wang, Zhixuan Chu, Shiyu Wang, Feiyue Ni, Ruihua Song, Chenyi Zhuang |
| 2024 | Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction. Wenzhao Jiang, Jindong Han, Hao Liu, Tao Tao, Naiqiang Tan, Hui Xiong |
| 2024 | Interpretable Transformer Hawkes Processes: Unveiling Complex Interactions in Social Networks. Zizhuo Meng, Ke Wan, Yadong Huang, Zhidong Li, Yang Wang, Feng Zhou |
| 2024 | Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. Kai Guo, Hongzhi Wen, Wei Jin, Yaming Guo, Jiliang Tang, Yi Chang |
| 2024 | Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks. Weijia Zhang, Le Zhang, Jindong Han, Hao Liu, Yanjie Fu, Jingbo Zhou, Yu Mei, Hui Xiong |
| 2024 | Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination. Ming Hu, Zhihao Yue, Xiaofei Xie, Cheng Chen, Yihao Huang, Xian Wei, Xiang Lian, Yang Liu, Mingsong Chen |
| 2024 | Item-Difficulty-Aware Learning Path Recommendation: From a Real Walking Perspective. Haotian Zhang, Shuanghong Shen, Bihan Xu, Zhenya Huang, Jinze Wu, Jing Sha, Shijin Wang |
| 2024 | Iterative Weak Learnability and Multiclass AdaBoost. In-Koo Cho, Jonathan A. Libgober, Cheng Ding |
| 2024 | Joint Auction in the Online Advertising Market. Zhen Zhang, Weian Li, Yahui Lei, Bingzhe Wang, Zhicheng Zhang, Qi Qi, Qiang Liu, Xingxing Wang |
| 2024 | KDD 2024 Finance Day. Guiling Wang, Daniel Borrajo |
| 2024 | KDD 2024 Special Day - AI for Environment. Karina Gibert, Wee Hyong Tok, Miquel Sànchez-Marrè |
| 2024 | KDD workshop on Evaluation and Trustworthiness of Generative AI Models. Yuan Ling, Shujing Dong, Yarong Feng, Zongyi Joe Liu, George Karypis, Chandan K. Reddy |
| 2024 | KiL 2024: 4th International Workshop on Knowledge-infused Learning Manas Gaur, Efthymia Tsamoura, Edward Raff, Nikhita Vedula, Srinivasan Parthasarathy |
| 2024 | Killing Two Birds with One Stone: Cross-modal Reinforced Prompting for Graph and Language Tasks. Wenyuan Jiang, Wenwei Wu, Le Zhang, Zixuan Yuan, Jian Xiang, Jingbo Zhou, Hui Xiong |
| 2024 | Know Your Needs Better: Towards Structured Understanding of Marketer Demands with Analogical Reasoning Augmented LLMs. Junjie Wang, Dan Yang, Binbin Hu, Yue Shen, Wen Zhang, Jinjie Gu |
| 2024 | Know in Xiaoyu Wang, Yonghui Guo, Hui Sheng, Peili Lv, Chi Zhou, Wei Huang, Shiqin Ta, Dongbo Huang, Xiujin Yang, Lan Xu, Hao Zhou, Yusheng Ji |
| 2024 | Know, Grow, and Protect Net Worth: Using ML for Asset Protection by Preventing Overdraft Fees. Avishek Kumar, Tyson Silver |
| 2024 | Knowledge Distillation with Perturbed Loss: From a Vanilla Teacher to a Proxy Teacher. Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Jialu Liu, Michael Bendersky, Marc Najork, Chao Zhang |
| 2024 | LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation. Rebecca Salganik, Xiaohao Liu, Yunshan Ma, Jian Kang, Tat-Seng Chua |
| 2024 | LASCA: A Large-Scale Stable Customer Segmentation Approach to Credit Risk Assessment. Yongfeng Gu, Yupeng Wu, Huakang Lu, Xingyu Lu, Hong Qian, Jun Zhou, Aimin Zhou |
| 2024 | LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs? Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Yijian Qin, Wenwu Zhu |
| 2024 | LPFormer: An Adaptive Graph Transformer for Link Prediction. Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang |
| 2024 | LaDe: The First Comprehensive Last-mile Express Dataset from Industry. Lixia Wu, Haomin Wen, Haoyuan Hu, Xiaowei Mao, Yutong Xia, Ergang Shan, Jianbin Zheng, Junhong Lou, Yuxuan Liang, Liuqing Yang, Roger Zimmermann, Youfang Lin, Huaiyu Wan |
| 2024 | Label Learning Method Based on Tensor Projection. Jing Li, Quanxue Gao, Qianqian Wang, Cheng Deng, De-Yan Xie |
| 2024 | Label Shift Correction via Bidirectional Marginal Distribution Matching. Ruidong Fan, Xiao Ouyang, Hong Tao, Chenping Hou |
| 2024 | Large Language Model with Curriculum Reasoning for Visual Concept Recognition. Yipeng Zhang, Xin Wang, Hong Chen, Jiapei Fan, Weigao Wen, Hui Xue, Hong Mei, Wenwu Zhu |
| 2024 | Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network. Lin Chen, Fengli Xu, Nian Li, Zhenyu Han, Meng Wang, Yong Li, Pan Hui |
| 2024 | Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System. Sein Kim, Hongseok Kang, Seungyoon Choi, Donghyun Kim, Min-Chul Yang, Chanyoung Park |
| 2024 | Large Scale Generative AI Text Applied to Sports and Music. Aaron K. Baughman, Eduardo Morales, Rahul Agarwal, Gozde Akay, Rogério Feris, Tony Johnson, Stephen Hammer, Leonid Karlinsky |
| 2024 | Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity. Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. Aditya Prakash |
| 2024 | Latent Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model. Yuxing Tian, Aiwen Jiang, Qi Huang, Jian Guo, Yiyan Qi |
| 2024 | Layer-Wise Adaptive Gradient Norm Penalizing Method for Efficient and Accurate Deep Learning. Sunwoo Lee |
| 2024 | LeMon: Automating Portrait Generation for Zero-Shot Story Visualization with Multi-Character Interactions. Ziyi Kou, Shichao Pei, Xiangliang Zhang |
| 2024 | Learn Together Stop Apart: An Inclusive Approach to Ensemble Pruning. Bulat Ibragimov, Gleb Gusev |
| 2024 | Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute. Tajima Shinji, Ren Sugihara, Ryota Kitahara, Masayuki Karasuyama |
| 2024 | Learning Causal Networks from Episodic Data. Osman Mian, Sarah Mameche, Jilles Vreeken |
| 2024 | Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data. Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield |
| 2024 | Learning Metrics that Maximise Power for Accelerated A/B-Tests. Olivier Jeunen, Aleksei Ustimenko |
| 2024 | Learning Multi-view Molecular Representations with Structured and Unstructured Knowledge. Yizhen Luo, Kai Yang, Massimo Hong, Xing Yi Liu, Zikun Nie, Hao Zhou, Zaiqing Nie |
| 2024 | Learning from Emergence: A Study on Proactively Inhibiting the Monosemantic Neurons of Artificial Neural Networks. Jiachuan Wang, Shimin Di, Lei Chen, Charles Wang Wai Ng |
| 2024 | Learning the Covariance of Treatment Effects Across Many Weak Experiments. Aurélien Bibaut, Winston Chou, Simon Ejdemyr, Nathan Kallus |
| 2024 | Learning to Bid the Interest Rate in Online Unsecured Personal Loans. Dong Jun Jee, Seung Jung Jin, Ji-Hoon Yoo, Byunggyu Ahn |
| 2024 | Learning to Rank for Maps at Airbnb. Malay Haldar, Hongwei Zhang, Kedar Bellare, Sherry Chen, Soumyadip Banerjee, Xiaotang Wang, Mustafa Abdool, Huiji Gao, Pavan Tapadia, Liwei He, Sanjeev Katariya |
| 2024 | Lessons Learned while Running ML Models in Harsh Environments. Pedro Bizarro |
| 2024 | Leveraging Exposure Networks for Detecting Fake News Sources. Maor Reuben, Lisa Friedland, Rami Puzis, Nir Grinberg |
| 2024 | Leveraging Pedagogical Theories to Understand Student Learning Process with Graph-based Reasonable Knowledge Tracing. Jiajun Cui, Hong Qian, Bo Jiang, Wei Zhang |
| 2024 | LiGNN: Graph Neural Networks at LinkedIn. Fedor Borisyuk, Shihai He, Yunbo Ouyang, Morteza Ramezani, Peng Du, Xiaochen Hou, Chengming Jiang, Nitin Pasumarthy, Priya Bannur, Birjodh Singh Tiwana, Ping Liu, Siddharth Dangi, Daqi Sun, Zhoutao Pei, Xiao Shi, Sirou Zhu, Qianqi Shen, Kuang-Hsuan Lee, David Stein, Baolei Li, Haichao Wei, Amol Ghoting, Souvik Ghosh |
| 2024 | LiMAML: Personalization of Deep Recommender Models via Meta Learning. Ruofan Wang, Prakruthi Prabhakar, Gaurav Srivastava, Tianqi Wang, Zeinab S. Jalali, Varun Bharill, Yunbo Ouyang, Aastha Nigam, Divya Venugopalan, Aman Gupta, Fedor Borisyuk, S. Sathiya Keerthi, Ajith Muralidharan |
| 2024 | LiRank: Industrial Large Scale Ranking Models at LinkedIn. Fedor Borisyuk, Mingzhou Zhou, Qingquan Song, Siyu Zhu, Birjodh Singh Tiwana, Ganesh Parameswaran, Siddharth Dangi, Lars Hertel, Qiang Charles Xiao, Xiaochen Hou, Yunbo Ouyang, Aman Gupta, Sheallika Singh, Dan Liu, Hailing Cheng, Lei Le, Jonathan Hung, S. Sathiya Keerthi, Ruoyan Wang, Fengyu Zhang, Mohit Kothari, Chen Zhu, Daqi Sun, Yun Dai, Xun Luan, Sirou Zhu, Zhiwei Wang, Neil Daftary, Qianqi Shen, Chengming Jiang, Haichao Wei, Maneesh Varshney, Amol Ghoting, Souvik Ghosh |
| 2024 | LogParser-LLM: Advancing Efficient Log Parsing with Large Language Models. Aoxiao Zhong, Dengyao Mo, Guiyang Liu, Jinbu Liu, Qingda Lu, Qi Zhou, Jiesheng Wu, Quanzheng Li, Qingsong Wen |
| 2024 | Logical Reasoning with Relation Network for Inductive Knowledge Graph Completion. Qinggang Zhang, Keyu Duan, Junnan Dong, Pai Zheng, Xiao Huang |
| 2024 | Long-Term Vessel Trajectory Imputation with Physics-Guided Diffusion Probabilistic Model. Zhiwen Zhang, Zipei Fan, Zewu Lv, Xuan Song, Ryosuke Shibasaki |
| 2024 | Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy. Yao Zhao, Zhitian Xie, Chen Liang, Chenyi Zhuang, Jinjie Gu |
| 2024 | Low Rank Multi-Dictionary Selection at Scale. Boya Ma, Maxwell McNeil, Abram Magner, Petko Bogdanov |
| 2024 | Lumos: Empowering Multimodal LLMs with Scene Text Recognition. Ashish Shenoy, Yichao Lu, Srihari Jayakumar, Debojeet Chatterjee, Mohsen Moslehpour, Pierce Chuang, Abhay Harpale, Vikas Bhardwaj, Di Xu, Shicong Zhao, Longfang Zhao, Ankit Ramchandani, Xin Luna Dong, Anuj Kumar |
| 2024 | MAML-en-LLM: Model Agnostic Meta-Training of LLMs for Improved In-Context Learning. Sanchit Sinha, Yuguang Yue, Victor Soto, Mayank Kulkarni, Jianhua Lu, Aidong Zhang |
| 2024 | MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer Recharge. Yuning Chen, Kang Yang, Zhiyu An, Brady Holder, Luke Paloutzian, Khaled M. Bali, Wan Du |
| 2024 | MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning. Bingchang Liu, Chaoyu Chen, Zi Gong, Cong Liao, Huan Wang, Zhichao Lei, Ming Liang, Dajun Chen, Min Shen, Hailian Zhou, Wei Jiang, Hang Yu, Jianguo Li |
| 2024 | MGMatch: Fast Matchmaking with Nonlinear Objective and Constraints via Multimodal Deep Graph Learning. Yu Sun, Kai Wang, Zhipeng Hu, Runze Wu, Yaoxin Wu, Wen Song, Xudong Shen, Tangjie Lv, Changjie Fan |
| 2024 | MISP: A Multimodal-based Intelligent Server Failure Prediction Model for Cloud Computing Systems. Xianting Lu, Yunong Wang, Yu Fu, Qi Sun, Xuhua Ma, Xudong Zheng, Cheng Zhuo |
| 2024 | MMBee: Live Streaming Gift-Sending Recommendations via Multi-Modal Fusion and Behaviour Expansion. Jiaxin Deng, Shiyao Wang, Yuchen Wang, Jiansong Qi, Liqin Zhao, Guorui Zhou, Gaofeng Meng |
| 2024 | MSPipe: Efficient Temporal GNN Training via Staleness-Aware Pipeline. Guangming Sheng, Junwei Su, Chao Huang, Chuan Wu |
| 2024 | Machine Learning for Clinical Management: From the Lab to the Hospital. Ricard Gavaldà |
| 2024 | Machine Learning in Finance. Leman Akoglu, Nitesh V. Chawla, Josep Domingo-Ferrer, Eren Kurshan, Senthil Kumar, Vidyut M. Naware, José A. Rodríguez-Serrano, Isha Chaturvedi, Saurabh Nagrecha, Mahashweta Das, Tanveer A. Faruquie |
| 2024 | MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading. Chuqiao Zong, Chaojie Wang, Molei Qin, Lei Feng, Xinrun Wang, Bo An |
| 2024 | Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask. Jingyu Xiao, Zhiyao Xu, Qingsong Zou, Qing Li, Dan Zhao, Dong Fang, Ruoyu Li, Wenxin Tang, Kang Li, Xudong Zuo, Penghui Hu, Yong Jiang, Zixuan Weng, Michael R. Lyu |
| 2024 | Making Temporal Betweenness Computation Faster and Restless. Filippo Brunelli, Pierluigi Crescenzi, Laurent Viennot |
| 2024 | Marrying Dialogue Systems with Data Visualization: Interactive Data Visualization Generation from Natural Language Conversations. Yuanfeng Song, Xuefang Zhao, Raymond Chi-Wing Wong |
| 2024 | Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain. Amin Karimi Monsefi, Payam Karisani, Mengxi Zhou, Stacey Choi, Nathan Doble, Heng Ji, Srinivasan Parthasarathy, Rajiv Ramnath |
| 2024 | Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization. Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Wei Cheng, Si Zhang, Yonghui Fan, Liqing Zhang, Dawei Zhou |
| 2024 | Max-Min Diversification with Asymmetric Distances. Iiro Kumpulainen, Florian Adriaens, Nikolaj Tatti |
| 2024 | Maximum-Entropy Regularized Decision Transformer with Reward Relabelling for Dynamic Recommendation. Xiaocong Chen, Siyu Wang, Lina Yao |
| 2024 | Measuring an LLM's Proficiency at using APIs: A Query Generation Strategy. Ying Sheng, Sudeep Gandhe, Bhargav Kanagal, Nick Edmonds, Zachary Fisher, Sandeep Tata, Aarush Selvan |
| 2024 | MemMap: An Adaptive and Latent Memory Structure for Dynamic Graph Learning. Shuo Ji, Mingzhe Liu, Leilei Sun, Chuanren Liu, Tongyu Zhu |
| 2024 | Meta Clustering of Neural Bandits. Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He |
| 2024 | Metric Decomposition in A/B Tests. Alex Deng, Luke Hagar, Nathaniel T. Stevens, Tatiana Xifara, Amit Gandhi |
| 2024 | Microservice Root Cause Analysis With Limited Observability Through Intervention Recognition in the Latent Space. Zhe Xie, Shenglin Zhang, Yitong Geng, Yao Zhang, Minghua Ma, Xiaohui Nie, Zhenhe Yao, Longlong Xu, Yongqian Sun, Wentao Li, Dan Pei |
| 2024 | Mining of Switching Sparse Networks for Missing Value Imputation in Multivariate Time Series. Kohei Obata, Koki Kawabata, Yasuko Matsubara, Yasushi Sakurai |
| 2024 | Mitigating Negative Transfer in Cross-Domain Recommendation via Knowledge Transferability Enhancement. Zijian Song, Wenhan Zhang, Lifang Deng, Jiandong Zhang, Zhihua Wu, Kaigui Bian, Bin Cui |
| 2024 | Mitigating Pooling Bias in E-commerce Search via False Negative Estimation. Xiaochen Wang, Xiao Xiao, Ruhan Zhang, Xuan Zhang, Taesik Na, Tejaswi Tenneti, Haixun Wang, Fenglong Ma |
| 2024 | Model-Agnostic Random Weighting for Out-of-Distribution Generalization. Yue He, Pengfei Tian, Renzhe Xu, Xinwei Shen, Xingxuan Zhang, Peng Cui |
| 2024 | Modeling User Retention through Generative Flow Networks. Ziru Liu, Shuchang Liu, Bin Yang, Zhenghai Xue, Qingpeng Cai, Xiangyu Zhao, Zijian Zhang, Lantao Hu, Han Li, Peng Jiang |
| 2024 | Money Never Sleeps: Maximizing Liquidity Mining Yields in Decentralized Finance. Wangze Ni, Yiwei Zhao, Weijie Sun, Lei Chen, Peng Cheng, Chen Jason Zhang, Xuemin Lin |
| 2024 | Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-level Anomaly Detection. Chunjing Xiao, Shikang Pang, Wenxin Tai, Yanlong Huang, Goce Trajcevski, Fan Zhou |
| 2024 | MulSTE: A Multi-view Spatio-temporal Learning Framework with Heterogeneous Event Fusion for Demand-supply Prediction. Li Lin, Zhiqiang Lu, Shuai Wang, Yunhuai Liu, Zhiqing Hong, Haotian Wang |
| 2024 | Multi-Behavior Collaborative Filtering with Partial Order Graph Convolutional Networks. Yijie Zhang, Yuanchen Bei, Hao Chen, Qijie Shen, Zheng Yuan, Huan Gong, Senzhang Wang, Feiran Huang, Xiao Huang |
| 2024 | Multi-Scale Detection of Anomalous Spatio-Temporal Trajectories in Evolving Trajectory Datasets. Chenhao Wang, Lisi Chen, Shuo Shang, Christian S. Jensen, Panos Kalnis |
| 2024 | Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization. Fei Liu, Xi Lin, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan |
| 2024 | Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. Yi Su, Haokai Lu, Yuening Li, Liang Liu, Shuchao Bi, Ed H. Chi, Minmin Chen |
| 2024 | Multi-modal Data Processing for Foundation Models: Practical Guidances and Use Cases. Daoyuan Chen, Yaliang Li, Bolin Ding |
| 2024 | Multi-objective Learning to Rank by Model Distillation. Jie Tang, Huiji Gao, Liwei He, Sanjeev Katariya |
| 2024 | Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang |
| 2024 | Multi-task Conditional Attention Network for Conversion Prediction in Logistics Advertising. Baoshen Guo, Xining Song, Shuai Wang, Wei Gong, Tian He, Xue Liu |
| 2024 | Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong |
| 2024 | Multivariate Log-based Anomaly Detection for Distributed Database. Lingzhe Zhang, Tong Jia, Mengxi Jia, Ying Li, Yong Yang, Zhonghai Wu |
| 2024 | Mutual Distillation Extracting Spatial-temporal Knowledge for Lightweight Multi-channel Sleep Stage Classification. Ziyu Jia, Haichao Wang, Yucheng Liu, Tianzi Jiang |
| 2024 | NL2Code-Reasoning and Planning with LLMs for Code Development. Ye Xing, Jun Huan, Wee Hyong Tok, Cong Shen, Johannes Gehrke, Katherine Lin, Arjun Guha, Omer Tripp, Murali Krishna Ramanathan |
| 2024 | Natural Language Explainable Recommendation with Robustness Enhancement. Jingsen Zhang, Jiakai Tang, Xu Chen, Wenhui Yu, Lantao Hu, Peng Jiang, Han Li |
| 2024 | Nested Fusion: A Method for Learning High Resolution Latent Structure of Multi-Scale Measurement Data on Mars. Austin P. Wright, Scott Davidoff, Duen Horng Chau |
| 2024 | Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models. Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu |
| 2024 | Neural Collapse Inspired Debiased Representation Learning for Min-max Fairness. Shenyu Lu, Junyi Chai, Xiaoqian Wang |
| 2024 | Neural Manifold Operators for Learning the Evolution of Physical Dynamics. Hao Wu, Kangyu Weng, Shuyi Zhou, Xiaomeng Huang, Wei Xiong |
| 2024 | Neural Optimization with Adaptive Heuristics for Intelligent Marketing System. Changshuai Wei, Benjamin Zelditch, Joyce Chen, Andre Assuncao Silva T. Ribeiro, Jingyi Kenneth Tay, Borja Ocejo Elizondo, Sathiya Keerthi Selvaraj, Aman Gupta, Licurgo Benemann De Almeida |
| 2024 | Neural Retrievers are Biased Towards LLM-Generated Content. Sunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu, Xiaolin Hu, Yong Liu, Xiao Zhang, Gang Wang, Jun Xu |
| 2024 | NeuroCut: A Neural Approach for Robust Graph Partitioning. Rishi Shah, Krishnanshu Jain, Sahil Manchanda, Sourav Medya, Sayan Ranu |
| 2024 | Next-generation Intelligent Assistants for Wearable Devices. Xin Luna Dong |
| 2024 | Noisy Label Removal for Partial Multi-Label Learning. Fuchao Yang, Yuheng Jia, Hui Liu, Yongqiang Dong, Junhui Hou |
| 2024 | Non-autoregressive Generative Models for Reranking Recommendation. Yuxin Ren, Qiya Yang, Yichun Wu, Wei Xu, Yalong Wang, Zhiqiang Zhang |
| 2024 | NudgeRank: Digital Algorithmic Nudging for Personalized Health. Jodi Chiam, Aloysius Lim, Ankur Teredesai |
| 2024 | OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining. Fanjin Zhang, Shijie Shi, Yifan Zhu, Bo Chen, Yukuo Cen, Jifan Yu, Yelin Chen, Lulu Wang, Qingfei Zhao, Yuqing Cheng, Tianyi Han, Yuwei An, Dan Zhang, Weng Lam Tam, Kun Cao, Yunhe Pang, Xinyu Guan, Huihui Yuan, Jian Song, Xiaoyan Li, Yuxiao Dong, Jie Tang |
| 2024 | ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education Systems. Hong Qian, Shuo Liu, Mingjia Li, Bingdong Li, Zhi Liu, Aimin Zhou |
| 2024 | Offline Imitation Learning with Model-based Reverse Augmentation. Jie-Jing Shao, Hao-Sen Shi, Lan-Zhe Guo, Yu-Feng Li |
| 2024 | Offline Reinforcement Learning for Optimizing Production Bidding Policies. Dmytro Korenkevych, Frank Cheng, Artsiom Balakir, Alex Nikulkov, Lingnan Gao, Zhihao Cen, Zuobing Xu, Zheqing Zhu |
| 2024 | On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top- Olivier Jeunen, Ivan Potapov, Aleksei Ustimenko |
| 2024 | On Early Detection of Hallucinations in Factual Question Answering. Ben Snyder, Marius Moisescu, Muhammad Bilal Zafar |
| 2024 | On Finding Bi-objective Pareto-optimal Fraud Prevention Rule Sets for Fintech Applications. Chengyao Wen, Yin Lou |
| 2024 | On the Convergence of Zeroth-Order Federated Tuning for Large Language Models. Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen |
| 2024 | One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen |
| 2024 | Online Drift Detection with Maximum Concept Discrepancy. Ke Wan, Yi Liang, Susik Yoon |
| 2024 | Online Preference Weight Estimation Algorithm with Vanishing Regret for Car-Hailing in Road Network. Yucen Gao, Zhehao Zhu, Mingqian Ma, Fei Gao, Hui Gao, Yangguang Shi, Xiaofeng Gao |
| 2024 | OntoType: Ontology-Guided and Pre-Trained Language Model Assisted Fine-Grained Entity Typing. Tanay Komarlu, Minhao Jiang, Xuan Wang, Jiawei Han |
| 2024 | Ontology Enrichment for Effective Fine-grained Entity Typing. Siru Ouyang, Jiaxin Huang, Pranav Pillai, Yunyi Zhang, Yu Zhang, Jiawei Han |
| 2024 | OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning. Rui Ye, Wenhao Wang, Jingyi Chai, Dihan Li, Zexi Li, Yinda Xu, Yaxin Du, Yanfeng Wang, Siheng Chen |
| 2024 | Optimized Cost Per Click in Online Advertising: A Theoretical Analysis. Kaichen Zhang, Zixuan Yuan, Hui Xiong |
| 2024 | Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement. Yakun Wang, Daixin Wang, Hongrui Liu, Binbin Hu, Yingcui Yan, Qiyang Zhang, Zhiqiang Zhang |
| 2024 | Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning. Amit Sharma, Hua Li, Xue Li, Jian Jiao |
| 2024 | Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models. Xu Shen, Yili Wang, Kaixiong Zhou, Shirui Pan, Xin Wang |
| 2024 | Optimizing Smartphone App Usage Prediction: A Click-Through Rate Ranking Approach. Yuqi Zhang, Meiying Kang, Xiucheng Li, Yu Qiu, Zhijun Li |
| 2024 | Orthogonality Matters: Invariant Time Series Representation for Out-of-distribution Classification. Ruize Shi, Hong Huang, Kehan Yin, Wei Zhou, Hai Jin |
| 2024 | Overview of ACM SIGKDD 2024 AI4Science4AI Special Day. Wei Ding, Gustau Camps-Valls |
| 2024 | PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization. Yuyang Ye, Lu-An Tang, Haoyu Wang, Runlong Yu, Wenchao Yu, Erhu He, Haifeng Chen, Hui Xiong |
| 2024 | PATE: Proximity-Aware Time Series Anomaly Evaluation. Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax |
| 2024 | PEMBOT: Pareto-Ensembled Multi-task Boosted Trees. Gokul Swamy, Anoop Saladi, Arunita Das, Shobhit Niranjan |
| 2024 | POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning. Junxiang Wang, Guangji Bai, Wei Cheng, Zhengzhang Chen, Liang Zhao, Haifeng Chen |
| 2024 | PSMC: Provable and Scalable Algorithms for Motif Conductance Based Graph Clustering. Longlong Lin, Tao Jia, Zeli Wang, Jin Zhao, Rong-Hua Li |
| 2024 | Path-Specific Causal Reasoning for Fairness-aware Cognitive Diagnosis. Dacao Zhang, Kun Zhang, Le Wu, Mi Tian, Richang Hong, Meng Wang |
| 2024 | Path-based Explanation for Knowledge Graph Completion. Heng Chang, Jiangnan Ye, Alejo Lopez-Avila, Jinhua Du, Jia Li |
| 2024 | Paths2Pair: Meta-path Based Link Prediction in Billion-Scale Commercial Heterogeneous Graphs. Jinquan Hang, Zhiqing Hong, Xinyue Feng, Guang Wang, Guang Yang, Feng Li, Xining Song, Desheng Zhang |
| 2024 | PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection. Ronghui Xu, Hao Miao, Senzhang Wang, Philip S. Yu, Jianxin Wang |
| 2024 | Performative Debias with Fair-exposure Optimization Driven by Strategic Agents in Recommender Systems. Zhichen Xiang, Hongke Zhao, Chuang Zhao, Ming He, Jianping Fan |
| 2024 | Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information. Aishwarya Jayagopal, Hansheng Xue, Ziyang He, Robert J. Walsh, Krishna Kumar Hariprasannan, David Shao Peng Tan, Tuan Zea Tan, Jason J. Pitt, Anand D. Jeyasekharan, Vaibhav Rajan |
| 2024 | Personalized Federated Continual Learning via Multi-Granularity Prompt. Hao Yu, Xin Yang, Xin Gao, Yan Kang, Hao Wang, Junbo Zhang, Tianrui Li |
| 2024 | Personalized Product Assortment with Real-time 3D Perception and Bayesian Payoff Estimation. Porter Jenkins, Michael Selander, J. Stockton Jenkins, Andrew Merrill, Kyle Armstrong |
| 2024 | Physics-informed Neural ODE for Post-disaster Mobility Recovery. Jiahao Li, Huandong Wang, Xinlei Chen |
| 2024 | Policy-Based Bayesian Active Causal Discovery with Deep Reinforcement Learning. Heyang Gao, Zexu Sun, Hao Yang, Xu Chen |
| 2024 | PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer. Jiahong Ma, Mingguo He, Zhewei Wei |
| 2024 | PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graph. Dazhou Yu, Yuntong Hu, Yun Li, Liang Zhao |
| 2024 | Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias. Miaomiao Cai, Lei Chen, Yifan Wang, Haoyue Bai, Peijie Sun, Le Wu, Min Zhang, Meng Wang |
| 2024 | Practical Machine Learning for Streaming Data. Heitor Murilo Gomes, Albert Bifet |
| 2024 | Practical Single Domain Generalization via Training-time and Test-time Learning. Shuai Yang, Zhen Zhang, Lichuan Gu |
| 2024 | Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks. Wenying Duan, Tianxiang Fang, Hong Rao, Xiaoxi He |
| 2024 | Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphs. Huanjing Zhao, Beining Yang, Yukuo Cen, Junyu Ren, Chenhui Zhang, Yuxiao Dong, Evgeny Kharlamov, Shu Zhao, Jie Tang |
| 2024 | Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation. Chen Wang, Ziwei Fan, Liangwei Yang, Mingdai Yang, Xiaolong Liu, Zhiwei Liu, Philip S. Yu |
| 2024 | Pre-train and Refine: Towards Higher Efficiency in K-Agnostic Community Detection without Quality Degradation. Meng Qin, Chaorui Zhang, Yu Gao, Weixi Zhang, Dit-Yan Yeung |
| 2024 | Pre-trained KPI Anomaly Detection Model Through Disentangled Transformer. Zhaoyang Yu, Changhua Pei, Xin Wang, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Xidao Wen, Jianhui Li, Gaogang Xie, Dan Pei |
| 2024 | Predicting Cascading Failures with a Hyperparametric Diffusion Model. Bin Xiang, Bogdan Cautis, Xiaokui Xiao, Olga Mula, Dusit Niyato, Laks V. S. Lakshmanan |
| 2024 | Predicting Long-term Dynamics of Complex Networks via Identifying Skeleton in Hyperbolic Space. Ruikun Li, Huandong Wang, Jinghua Piao, Qingmin Liao, Yong Li |
| 2024 | Preventing Strategic Behaviors in Collaborative Inference for Vertical Federated Learning. Yidan Xing, Zhenzhe Zheng, Fan Wu |
| 2024 | Privacy-Preserved Neural Graph Databases. Qi Hu, Haoran Li, Jiaxin Bai, Zihao Wang, Yangqiu Song |
| 2024 | Privacy-Preserving Federated Learning using Flower Framework. Mohammad Naseri, Javier Fernández-Marqués, Yan Gao, Heng Pan |
| 2024 | Privileged Knowledge State Distillation for Reinforcement Learning-based Educational Path Recommendation. Qingyao Li, Wei Xia, Li'ang Yin, Jiarui Jin, Yong Yu |
| 2024 | ProCom: A Few-shot Targeted Community Detection Algorithm. Xixi Wu, Kaiyu Xiong, Yun Xiong, Xiaoxin He, Yao Zhang, Yizhu Jiao, Jiawei Zhang |
| 2024 | Probabilistic Attention for Sequential Recommendation. Yuli Liu, Christian Walder, Lexing Xie, Yiqun Liu |
| 2024 | Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2024, Barcelona, Spain, August 25-29, 2024 Ricardo Baeza-Yates, Francesco Bonchi |
| 2024 | Profiling Urban Streets: A Semi-Supervised Prediction Model Based on Street View Imagery and Spatial Topology. Meng Chen, Zechen Li, Weiming Huang, Yongshun Gong, Yilong Yin |
| 2024 | Promoting Fairness and Priority in Selecting Md Mouinul Islam, Soroush Vahidi, Baruch Schieber, Senjuti Basu Roy |
| 2024 | Prompt Perturbation in Retrieval-Augmented Generation based Large Language Models. Zhibo Hu, Chen Wang, Yanfeng Shu, Hye-Young Paik, Liming Zhu |
| 2024 | Propagation Structure-Aware Graph Transformer for Robust and Interpretable Fake News Detection. Junyou Zhu, Chao Gao, Ze Yin, Xianghua Li, Jürgen Kurths |
| 2024 | ProtoMix: Augmenting Health Status Representation Learning via Prototype-based Mixup. Yongxin Xu, Xinke Jiang, Xu Chu, Yuzhen Xiao, Chaohe Zhang, Hongxin Ding, Junfeng Zhao, Yasha Wang, Bing Xie |
| 2024 | Provable Adaptivity of Adam under Non-uniform Smoothness. Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen |
| 2024 | QGRL: Quaternion Graph Representation Learning for Heterogeneous Feature Data Clustering. Junyang Chen, Yuzhu Ji, Rong Zou, Yiqun Zhang, Yiu-ming Cheung |
| 2024 | QSketch: An Efficient Sketch for Weighted Cardinality Estimation in Streams. Yiyan Qi, Rundong Li, Pinghui Wang, Yufang Sun, Rui Xing |
| 2024 | Quantifying and Estimating the Predictability Upper Bound of Univariate Numeric Time Series. Jamal Mohammed, Michael H. Böhlen, Sven Helmer |
| 2024 | R-Eval: A Unified Toolkit for Evaluating Domain Knowledge of Retrieval Augmented Large Language Models. Shangqing Tu, Yuanchun Wang, Jifan Yu, Yuyang Xie, Yaran Shi, Xiaozhi Wang, Jing Zhang, Lei Hou, Juanzi Li |
| 2024 | RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression Tasks. Seonghyeon Hwang, Minsu Kim, Steven Euijong Whang |
| 2024 | RCTD: Reputation-Constrained Truth Discovery in Sybil Attack Crowdsourcing Environment. Xing Jin, Zhihai Gong, Jiuchuan Jiang, Chao Wang, Jian Zhang, Zhen Wang |
| 2024 | RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. Luis Roque, Carlos Soares, Luís Torgo |
| 2024 | RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes. Xiaoshan Yu, Chuan Qin, Dazhong Shen, Shangshang Yang, Haiping Ma, Hengshu Zhu, Xingyi Zhang |
| 2024 | RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning. Congyun Jin, Ming Zhang, Weixiao Ma, Yujiao Li, Yingbo Wang, Yabo Jia, Yuliang Du, Tao Sun, Haowen Wang, Cong Fan, Jinjie Gu, Chenfei Chi, Xiangguo Lv, Fangzhou Li, Wei Xue, Yiran Huang |
| 2024 | ROTAN: A Rotation-based Temporal Attention Network for Time-Specific Next POI Recommendation. Shanshan Feng, Feiyu Meng, Lisi Chen, Shuo Shang, Yew Soon Ong |
| 2024 | RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data. Chin-Chia Michael Yeh, Yujie Fan, Xin Dai, Uday Singh Saini, Vivian Lai, Prince Osei Aboagye, Junpeng Wang, Huiyuan Chen, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang |
| 2024 | Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing. Bowei He, Yunpeng Weng, Xing Tang, Ziqiang Cui, Zexu Sun, Liang Chen, Xiuqiang He, Chen Ma |
| 2024 | Ranking with Slot Constraints. Wentao Guo, Andrew Wang, Bradon Thymes, Thorsten Joachims |
| 2024 | RareBench: Can LLMs Serve as Rare Diseases Specialists? Xuanzhong Chen, Xiaohao Mao, Qihan Guo, Lun Wang, Shuyang Zhang, Ting Chen |
| 2024 | ReCDA: Concept Drift Adaptation with Representation Enhancement for Network Intrusion Detection. Shuo Yang, Xinran Zheng, Jinze Li, Jinfeng Xu, Xingjun Wang, Edith C. H. Ngai |
| 2024 | ReCTSi: Resource-efficient Correlated Time Series Imputation via Decoupled Pattern Learning and Completeness-aware Attentions. Zhichen Lai, Dalin Zhang, Huan Li, Dongxiang Zhang, Hua Lu, Christian S. Jensen |
| 2024 | ReFound: Crafting a Foundation Model for Urban Region Understanding upon Language and Visual Foundations. Congxi Xiao, Jingbo Zhou, Yixiong Xiao, Jizhou Huang, Hui Xiong |
| 2024 | Reasoning and Planning with Large Language Models in Code Development. Hao Ding, Ziwei Fan, Ingo Gühring, Gaurav Gupta, Wooseok Ha, Jun Huan, Linbo Liu, Behrooz Omidvar-Tehrani, Shiqi Wang, Hao Zhou |
| 2024 | RecExplainer: Aligning Large Language Models for Explaining Recommendation Models. Yuxuan Lei, Jianxun Lian, Jing Yao, Xu Huang, Defu Lian, Xing Xie |
| 2024 | Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning. Michal Derezinski, Michael W. Mahoney |
| 2024 | Reimagining Graph Classification from a Prototype View with Optimal Transport: Algorithm and Theorem. Chen Qian, Huayi Tang, Hong Liang, Yong Liu |
| 2024 | Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness. Dingrong Wang, Hitesh Sapkota, Zhiqiang Tao, Qi Yu |
| 2024 | RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery. Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu |
| 2024 | Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Broad Physical Dynamics Learning. Zinan Zheng, Yang Liu, Jia Li, Jianhua Yao, Yu Rong |
| 2024 | Relevance Meets Diversity: A User-Centric Framework for Knowledge Exploration Through Recommendations. Erica Coppolillo, Giuseppe Manco, Aristides Gionis |
| 2024 | Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I. Harrie Oosterhuis, Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky |
| 2024 | Repeat-Aware Neighbor Sampling for Dynamic Graph Learning. Tao Zou, Yuhao Mao, Junchen Ye, Bowen Du |
| 2024 | Representation Learning of Geometric Trees. Zheng Zhang, Allen Zhang, Ruth Nelson, Giorgio A. Ascoli, Liang Zhao |
| 2024 | Representation Learning of Temporal Graphs with Structural Roles. Huaming Du, Long Shi, Xingyan Chen, Yu Zhao, Hegui Zhang, Carl Yang, Fuzhen Zhuang, Gang Kou |
| 2024 | Reserving-Masking-Reconstruction Model for Self-Supervised Heterogeneous Graph Representation. Haoran Duan, Cheng Xie, Linyu Li |
| 2024 | Residual Multi-Task Learner for Applied Ranking. Cong Fu, Kun Wang, Jiahua Wu, Yizhou Chen, Guangda Huzhang, Yabo Ni, Anxiang Zeng, Zhiming Zhou |
| 2024 | Resilient k-Clustering. Sara Ahmadian, MohammadHossein Bateni, Hossein Esfandiari, Silvio Lattanzi, Morteza Monemizadeh, Ashkan Norouzi-Fard |
| 2024 | Responsible AI Day. Ricardo Baeza-Yates, Nataly Buslón |
| 2024 | Resurrecting Label Propagation for Graphs with Heterophily and Label Noise. Yao Cheng, Caihua Shan, Yifei Shen, Xiang Li, Siqiang Luo, Dongsheng Li |
| 2024 | Rethinking Fair Graph Neural Networks from Re-balancing. Zhixun Li, Yushun Dong, Qiang Liu, Jeffrey Xu Yu |
| 2024 | Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang |
| 2024 | Rethinking Order Dispatching in Online Ride-Hailing Platforms. Zhaoxing Yang, Haiming Jin, Guiyun Fan, Min Lu, Yiran Liu, Xinlang Yue, Hao Pan, Zhe Xu, Guobin Wu, Qun Li, Xiaotong Wang, Jiecheng Guo |
| 2024 | Retrieval-Augmented Hypergraph for Multimodal Social Media Popularity Prediction. Zhangtao Cheng, Jienan Zhang, Xovee Xu, Goce Trajcevski, Ting Zhong, Fan Zhou |
| 2024 | Revisiting Local PageRank Estimation on Undirected Graphs: Simple and Optimal. Hanzhi Wang |
| 2024 | Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen |
| 2024 | Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method. Chen Yang, Sunhao Dai, Yupeng Hou, Wayne Xin Zhao, Jun Xu, Yang Song, Hengshu Zhu |
| 2024 | Robust Auto-Bidding Strategies for Online Advertising. Qilong Lin, Zhenzhe Zheng, Fan Wu |
| 2024 | Robust Predictions with Ambiguous Time Delays: A Bootstrap Strategy. Jiajie Wang, Zhiyuan Jerry Lin, Wen Chen |
| 2024 | Rotative Factorization Machines. Zhen Tian, Yuhong Shi, Xiangkun Wu, Wayne Xin Zhao, Ji-Rong Wen |
| 2024 | RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network. Yunbo Hou, Haoran Ye, Yingxue Zhang, Siyuan Xu, Guojie Song |
| 2024 | Routing Evidence for Unseen Actions in Video Moment Retrieval. Guolong Wang, Xun Wu, Zheng Qin, Liangliang Shi |
| 2024 | SEBot: Structural Entropy Guided Multi-View Contrastive learning for Social Bot Detection. Yingguang Yang, Qi Wu, Buyun He, Hao Peng, Renyu Yang, Zhifeng Hao, Yong Liao |
| 2024 | SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning. Kaidi Li, Tianmeng Yang, Min Zhou, Jiahao Meng, Shendi Wang, Yihui Wu, Boshuai Tan, Hu Song, Lujia Pan, Fan Yu, Zhenli Sheng, Yunhai Tong |
| 2024 | SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning. Jongha Lee, Sunwoo Kim, Kijung Shin |
| 2024 | STATE: A Robust ATE Estimator of Heavy-Tailed Metrics for Variance Reduction in Online Controlled Experiments. Hao Zhou, Kun Sun, Shaoming Li, Yangfeng Fan, Guibin Jiang, Jiaqi Zheng, Tao Li |
| 2024 | STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning. Wei Shao, Yufan Kang, Ziyan Peng, Xiao Xiao, Lei Wang, Yuhui Yang, Flora D. Salim |
| 2024 | STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts. Binwu Wang, Jiaming Ma, Pengkun Wang, Xu Wang, Yudong Zhang, Zhengyang Zhou, Yang Wang |
| 2024 | Scalable Algorithm for Finding Balanced Subgraphs with Tolerance in Signed Networks. Jingbang Chen, Qiuyang Mang, Hangrui Zhou, Richard Peng, Yu Gao, Chenhao Ma |
| 2024 | Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior. Pingchuan Ma, Rui Ding, Qiang Fu, Jiaru Zhang, Shuai Wang, Shi Han, Dongmei Zhang |
| 2024 | Scalable Graph Learning for your Enterprise. Hema Raghavan |
| 2024 | Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity. Dongyue Li, Aneesh Sharma, Hongyang R. Zhang |
| 2024 | Scalable Rule Lists Learning with Sampling. Leonardo Pellegrina, Fabio Vandin |
| 2024 | Scalable Temporal Motif Densest Subnetwork Discovery. Ilie Sarpe, Fabio Vandin, Aristides Gionis |
| 2024 | Scaling Training Data with Lossy Image Compression. Katherine L. Mentzer, Andrea Montanari |
| 2024 | Self-Distilled Disentangled Learning for Counterfactual Prediction. Xinshu Li, Mingming Gong, Lina Yao |
| 2024 | Self-Explainable Temporal Graph Networks based on Graph Information Bottleneck. Sangwoo Seo, Sungwon Kim, Jihyeong Jung, Yoonho Lee, Chanyoung Park |
| 2024 | Self-Supervised Denoising through Independent Cascade Graph Augmentation for Robust Social Recommendation. Youchen Sun, Zhu Sun, Yingpeng Du, Jie Zhang, Yew Soon Ong |
| 2024 | Self-Supervised Learning for Graph Dataset Condensation. Yuxiang Wang, Xiao Yan, Shiyu Jin, Hao Huang, Quanqing Xu, Qingchen Zhang, Bo Du, Jiawei Jiang |
| 2024 | Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask. Zineb Senane, Lele Cao, Valentin Leonhard Buchner, Yusuke Tashiro, Lei You, Pawel Andrzej Herman, Mats Nordahl, Ruibo Tu, Vilhelm von Ehrenheim |
| 2024 | Self-consistent Deep Geometric Learning for Heterogeneous Multi-source Spatial Point Data Prediction. Dazhou Yu, Xiaoyun Gong, Yun Li, Meikang Qiu, Liang Zhao |
| 2024 | Semi-Supervised Learning for Time Series Collected at a Low Sampling Rate. Minyoung Bae, Yooju Shin, Youngeun Nam, Youngseop Lee, Jae-Gil Lee |
| 2024 | SensitiveHUE: Multivariate Time Series Anomaly Detection by Enhancing the Sensitivity to Normal Patterns. Yuye Feng, Wei Zhang, Yao Fu, Weihao Jiang, Jiang Zhu, Wenqi Ren |
| 2024 | SentHYMNent: An Interpretable and Sentiment-Driven Model for Algorithmic Melody Harmonization. Stephen Hahn, Jerry Yin, Rico Zhu, Weihan Xu, Yue Jiang, Simon Mak, Cynthia Rudin |
| 2024 | SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing. Changchang Yin, Pin-Yu Chen, Bingsheng Yao, Dakuo Wang, Jeffrey M. Caterino, Ping Zhang |
| 2024 | ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification. Xuan-May Le, Ling Luo, Uwe Aickelin, Minh-Tuan Tran |
| 2024 | Sharing is Caring: A Practical Guide to FAIR(ER) Open Data Release. Amelia Henriksen, Miranda Mundt |
| 2024 | Shopping Trajectory Representation Learning with Pre-training for E-commerce Customer Understanding and Recommendation. Yankai Chen, Quoc-Tuan Truong, Xin Shen, Jin Li, Irwin King |
| 2024 | SiGeo: Sub-One-Shot NAS via Geometry of Loss Landscape. Hua Zheng, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Wen-Yen Chen, Wei Wen |
| 2024 | SimDiff: Simple Denoising Probabilistic Latent Diffusion Model for Data Augmentation on Multi-modal Knowledge Graph. Ran Li, Shimin Di, Lei Chen, Xiaofang Zhou |
| 2024 | Sketch-Based Replay Projection for Continual Learning. Jack Julian, Yun Sing Koh, Albert Bifet |
| 2024 | Source Localization for Cross Network Information Diffusion. Chen Ling, Tanmoy Chowdhury, Jie Ji, Sirui Li, Andreas Züfle, Liang Zhao |
| 2024 | Spatio-Temporal Consistency Enhanced Differential Network for Interpretable Indoor Temperature Prediction. Dekang Qi, Xiuwen Yi, Chengjie Guo, Yanyong Huang, Junbo Zhang, Tianrui Li, Yu Zheng |
| 2024 | Spending Programmed Bidding: Privacy-friendly Bid Optimization with ROI Constraint in Online Advertising. Yumin Su, Min Xiang, Yifei Chen, Yanbiao Li, Tian Qin, Hongyi Zhang, Yasong Li, Xiaobing Liu |
| 2024 | Spuriousness-Aware Meta-Learning for Learning Robust Classifiers. Guangtao Zheng, Wenqian Ye, Aidong Zhang |
| 2024 | Statistical Models of Top- Amel Awadelkarim, Johan Ugander |
| 2024 | Subspace Selection based Prompt Tuning with Nonconvex Nonsmooth Black-Box Optimization. Haozhen Zhang, Hualin Zhang, Bin Gu, Yi Chang |
| 2024 | Symbolic Regression: A Pathway to Interpretability Towards Automated Scientific Discovery. Nour Makke, Sanjay Chawla |
| 2024 | Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models. Yuan Zhong, Xiaochen Wang, Jiaqi Wang, Xiaokun Zhang, Yaqing Wang, Mengdi Huai, Cao Xiao, Fenglong Ma |
| 2024 | Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods. Da Yan, Lyuheng Yuan, Akhlaque Ahmad, Chenguang Zheng, Hongzhi Chen, James Cheng |
| 2024 | TACCO: Task-guided Co-clustering of Clinical Concepts and Patient Visits for Disease Subtyping based on EHR Data. Ziyang Zhang, Hejie Cui, Ran Xu, Yuzhang Xie, Joyce C. Ho, Carl Yang |
| 2024 | TDNetGen: Empowering Complex Network Resilience Prediction with Generative Augmentation of Topology and Dynamics. Chang Liu, Jingtao Ding, Yiwen Song, Yong Li |
| 2024 | TSC: A Simple Two-Sided Constraint against Over-Smoothing. Furong Peng, Kang Liu, Xuan Lu, Yuhua Qian, HongRen Yan, Chao Ma |
| 2024 | TSMO 2024: Two-sided Marketplace Optimization. Mihajlo Grbovic, Vladan Radosavljevic, Minmin Chen, Katerina Iliakopoulou-Zanos, Thanasis Noulas, Amit Goyal, Fabrizio Silvestri |
| 2024 | Tackling Concept Shift in Text Classification using Entailment-style Modeling. Sumegh Roychowdhury, Karan Gupta, Siva Rajesh Kasa, Prasanna Srinivasa Murthy |
| 2024 | Tackling Instance-Dependent Label Noise with Class Rebalance and Geometric Regularization. Shuzhi Cao, Jianfei Ruan, Bo Dong, Bin Shi |
| 2024 | Team up GBDTs and DNNs: Advancing Efficient and Effective Tabular Prediction with Tree-hybrid MLPs. Jiahuan Yan, Jintai Chen, Qianxing Wang, Danny Z. Chen, Jian Wu |
| 2024 | Television Discourse Decoded: Comprehensive Multimodal Analytics at Scale. Anmol Agarwal, Pratyush Priyadarshi, Shiven Sinha, Shrey Gupta, Hitkul Jangra, Ponnurangam Kumaraguru, Kiran Garimella |
| 2024 | Temporal Prototype-Aware Learning for Active Voltage Control on Power Distribution Networks. Feiyang Xu, Shunyu Liu, Yunpeng Qing, Yihe Zhou, Yuwen Wang, Mingli Song |
| 2024 | Temporal Uplift Modeling for Online Marketing. Xin Zhang, Kai Wang, Zengmao Wang, Bo Du, Shiwei Zhao, Runze Wu, Xudong Shen, Tangjie Lv, Changjie Fan |
| 2024 | Tensorized Unaligned Multi-view Clustering with Multi-scale Representation Learning. Jintian Ji, Songhe Feng, Yidong Li |
| 2024 | Text Matching Indexers in Taobao Search. Sen Li, Fuyu Lv, Ruqing Zhang, Dan Ou, Zhixuan Zhang, Maarten de Rijke |
| 2024 | The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2024 | The 13th International Workshop on Urban Computing. Yuxuan Liang, Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson |
| 2024 | The 2nd International Workshop: From Innovation to Scale (I2S) - Successfully Build, Commercialize, and Scale AI Innovations. Ankur Teredesai, Michael Zeller, Mohak Shah, Shenghua Bao, Wee Hyong Tok, Linsey Pang |
| 2024 | The 4 Steven Ullman, Benjamin M. Ampel, Sagar Samtani, Shanchieh Yang, Hsinchun Chen |
| 2024 | The 4th KDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial'24). Zhe Jiang, Liang Zhao, Xun Zhou, Junbo Zhang, Shashi Shekhar, Jieping Ye |
| 2024 | The 5th International Workshop on Talent and Management Computing (TMC'2024). Hengshu Zhu, Yong Ge, Hui Xiong, Ee-Peng Lim |
| 2024 | The First Workshop on AI Behavioral Science. Himabindu Lakkaraju, Qiaozhu Mei, Chenhao Tan, Jie Tang, Yutong Xie |
| 2024 | The Fourth International Workshop on Smart Data for Blockchain and Distributed Ledger (SDBD'24). Feida Zhu, Jian Pei, Michael Zeller, Bingxue Zhang |
| 2024 | The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs. Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang |
| 2024 | The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field. Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Junfeng Fang, Xiaojiang Peng, Yuxuan Liang, Yang Wang |
| 2024 | The Third Workshop on Applied Machine Learning Management. Dmitri Goldenberg, Shir Meir Lador, Elena Sokolova, Lin Lee Cheong, Mohak Sukhwani, Saloni Potdar |
| 2024 | Time-Aware Attention-Based Transformer (TAAT) for Cloud Computing System Failure Prediction. Lingfei Deng, Yunong Wang, Haoran Wang, Xuhua Ma, Xiaoming Du, Xudong Zheng, Dongrui Wu |
| 2024 | TnT-LLM: Text Mining at Scale with Large Language Models. Mengting Wan, Tara Safavi, Sujay Kumar Jauhar, Yujin Kim, Scott Counts, Jennifer Neville, Siddharth Suri, Chirag Shah, Ryen W. White, Longqi Yang, Reid Andersen, Georg Buscher, Dhruv Joshi, Nagu Rangan |
| 2024 | Top-Down Bayesian Posterior Sampling for Sum-Product Networks. Soma Yokoi, Issei Sato |
| 2024 | Topology-Driven Multi-View Clustering via Tensorial Refined Sigmoid Rank Minimization. Zhibin Gu, Zhendong Li, Songhe Feng |
| 2024 | Topology-aware Embedding Memory for Continual Learning on Expanding Networks. Xikun Zhang, Dongjin Song, Yixin Chen, Dacheng Tao |
| 2024 | Topology-monitorable Contrastive Learning on Dynamic Graphs. Zulun Zhu, Kai Wang, Haoyu Liu, Jintang Li, Siqiang Luo |
| 2024 | Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach. Yicong Li, Yu Yang, Jiannong Cao, Shuaiqi Liu, Haoran Tang, Guandong Xu |
| 2024 | Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling. Siwei Zhang, Xi Chen, Yun Xiong, Xixi Wu, Yao Zhang, Yongrui Fu, Yinglong Zhao, Jiawei Zhang |
| 2024 | Towards Automatic Evaluation for LLMs' Clinical Capabilities: Metric, Data, and Algorithm. Lei Liu, Xiaoyan Yang, Fangzhou Li, Chenfei Chi, Yue Shen, Shiwei Lyu, Ming Zhang, Xiaowei Ma, Xiangguo Lv, Liya Ma, Zhiqiang Zhang, Wei Xue, Yiran Huang, Jinjie Gu |
| 2024 | Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification. Beini Xie, Heng Chang, Ziwei Zhang, Zeyang Zhang, Simin Wu, Xin Wang, Yuan Meng, Wenwu Zhu |
| 2024 | Towards Robust Information Extraction via Binomial Distribution Guided Counterpart Sequence. Yinhao Bai, Yuhua Zhao, Zhixin Han, Hang Gao, Chao Xue, Mengting Hu |
| 2024 | Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning. Jiakai Tang, Sunhao Dai, Zexu Sun, Xu Chen, Jun Xu, Wenhui Yu, Lantao Hu, Peng Jiang, Han Li |
| 2024 | Towards Test Time Adaptation via Calibrated Entropy Minimization. Hao Yang, Min Wang, Jinshen Jiang, Yun Zhou |
| 2024 | TrajRecovery: An Efficient Vehicle Trajectory Recovery Framework based on Urban-Scale Traffic Camera Records. Dongen Wu, Ziquan Fang, Qichen Sun, Lu Chen, Haiyang Hu, Fei Wang, Yunjun Gao |
| 2024 | Transportation Marketplace Rate Forecast Using Signature Transform. Haotian Gu, Xin Guo, Timothy L. Jacobs, Philip M. Kaminsky, Xinyu Li |
| 2024 | Trinity: Syncretizing Multi-/Long-Tail/Long-Term Interests All in One. Jing Yan, Liu Jiang, Jianfei Cui, Zhichen Zhao, Xingyan Bin, Feng Zhang, Zuotao Liu |
| 2024 | Truthful Bandit Mechanisms for Repeated Two-stage Ad Auctions. Haoming Li, Yumou Liu, Zhenzhe Zheng, Zhilin Zhang, Jian Xu, Fan Wu |
| 2024 | URRL-IMVC: Unified and Robust Representation Learning for Incomplete Multi-View Clustering. Ge Teng, Ting Mao, Chen Shen, Xiang Tian, Xuesong Liu, Yaowu Chen, Jieping Ye |
| 2024 | Understanding Inter-Session Intentions via Complex Logical Reasoning. Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Yangqiu Song |
| 2024 | Understanding the Ranking Loss for Recommendation with Sparse User Feedback. Zhutian Lin, Junwei Pan, Shangyu Zhang, Ximei Wang, Xi Xiao, Shudong Huang, Lei Xiao, Jie Jiang |
| 2024 | Understanding the Weakness of Large Language Model Agents within a Complex Android Environment. Mingzhe Xing, Rongkai Zhang, Hui Xue, Qi Chen, Fan Yang, Zhen Xiao |
| 2024 | UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction. Yuan Yuan, Jingtao Ding, Jie Feng, Depeng Jin, Yong Li |
| 2024 | Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation. Yuting Zhang, Yiqing Wu, Ruidong Han, Ying Sun, Yongchun Zhu, Xiang Li, Wei Lin, Fuzhen Zhuang, Zhulin An, Yongjun Xu |
| 2024 | Unified Low-rank Compression Framework for Click-through Rate Prediction. Hao Yu, Minghao Fu, Jiandong Ding, Yusheng Zhou, Jianxin Wu |
| 2024 | Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals. Bardh Prenkaj, Mario Villaizán-Vallelado, Tobias Leemann, Gjergji Kasneci |
| 2024 | Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering. Yihong Wu, Le Zhang, Fengran Mo, Tianyu Zhu, Weizhi Ma, Jian-Yun Nie |
| 2024 | Unraveling Block Maxima Forecasting Models with Counterfactual Explanation. Yue Deng, Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo |
| 2024 | Unsupervised Alignment of Hypergraphs with Different Scales. Manh Tuan Do, Kijung Shin |
| 2024 | Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning. Wangyang Ying, Dongjie Wang, Xuanming Hu, Yuanchun Zhou, Charu C. Aggarwal, Yanjie Fu |
| 2024 | Unsupervised Heterogeneous Graph Rewriting Attack via Node Clustering. Haosen Wang, Can Xu, Chenglong Shi, Pengfei Zheng, Shiming Zhang, Minhao Cheng, Hongyang Chen |
| 2024 | Unsupervised Ranking Ensemble Model for Recommendation. Wenhui Yu, Bingqi Liu, Bin Xia, Xiaoxiao Xu, Ying Chen, Yongchang Li, Lantao Hu |
| 2024 | Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks. Yuwen Wang, Shunyu Liu, Tongya Zheng, Kaixuan Chen, Mingli Song |
| 2024 | Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data. Hanyang Yuan, Jiarong Xu, Cong Wang, Ziqi Yang, Chunping Wang, Keting Yin, Yang Yang |
| 2024 | Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks. Zongwei Wang, Junliang Yu, Min Gao, Hongzhi Yin, Bin Cui, Shazia Sadiq |
| 2024 | Uplift Modelling via Gradient Boosting. Bulat Ibragimov, Anton Vakhrushev |
| 2024 | Urban Foundation Models: A Survey. Weijia Zhang, Jindong Han, Zhao Xu, Hang Ni, Hao Liu, Hui Xiong |
| 2024 | Urban-Focused Multi-Task Offline Reinforcement Learning with Contrastive Data Sharing. Xinbo Zhao, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Yanhua Li, Jun Luo |
| 2024 | UrbanGPT: Spatio-Temporal Large Language Models. Zhonghang Li, Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, Chao Huang |
| 2024 | User Welfare Optimization in Recommender Systems with Competing Content Creators. Fan Yao, Yiming Liao, Mingzhe Wu, Chuanhao Li, Yan Zhu, James Yang, Jingzhou Liu, Qifan Wang, Haifeng Xu, Hongning Wang |
| 2024 | Using Self-supervised Learning Can Improve Model Fairness. Sofia Yfantidou, Dimitris Spathis, Marios Constantinides, Athena Vakali, Daniele Quercia, Fahim Kawsar |
| 2024 | Valuing an Engagement Surface using a Large Scale Dynamic Causal Model. Abhimanyu Mukerji, Sushant More, Ashwin Viswanathan Kannan, Lakshmi Ravi, Hua Chen, Naman Kohli, Chris Khawand, Dinesh Mandalapu |
| 2024 | VecAug: Unveiling Camouflaged Frauds with Cohort Augmentation for Enhanced Detection. Fei Xiao, Shaofeng Cai, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Meihui Zhang |
| 2024 | VertiMRF: Differentially Private Vertical Federated Data Synthesis. Fangyuan Zhao, Zitao Li, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li |
| 2024 | Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions. Yaqing Wang, Hongming Piao, Daxiang Dong, Quanming Yao, Jingbo Zhou |
| 2024 | Weather Knows What Will Occur: Urban Public Nuisance Events Prediction and Control with Meteorological Assistance. Yi Xie, Tianyu Qiu, Yun Xiong, Xiuqi Huang, Xiaofeng Gao, Chao Chen, Qiang Wang, Haihong Li |
| 2024 | When Box Meets Graph Neural Network in Tag-aware Recommendation. Fake Lin, Ziwei Zhao, Xi Zhu, Da Zhang, Shitian Shen, Xueying Li, Tong Xu, Suojuan Zhang, Enhong Chen |
| 2024 | Where Have You Been? A Study of Privacy Risk for Point-of-Interest Recommendation. Kunlin Cai, Jinghuai Zhang, Zhiqing Hong, William Shand, Guang Wang, Desheng Zhang, Jianfeng Chi, Yuan Tian |
| 2024 | Workshop on Deep Learning and Large Language Models for Knowledge Graphs (DL4KG). Mehwish Alam, Davide Buscaldi, Michael Cochez, Genet Asefa Gesese, Francesco Osborne, Diego Reforgiato Recupero |
| 2024 | Workshop on Discovering Drift Phenomena in Evolving Data Landscape (DELTA). Marco Piangerelli, Bardh Prenkaj, Ylenia Rotalinti, Ananya Joshi, Giovanni Stilo |
| 2024 | Workshop on Human-Interpretable AI. Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Francesco Giannini, Zohreh Shams, Damien Garreau, Mateja Jamnik, Tania Cerquitelli |
| 2024 | XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques. Yu Xiong, Zhipeng Hu, Ye Huang, Runze Wu, Kai Guan, Xingchen Fang, Ji Jiang, Tianze Zhou, Yujing Hu, Haoyu Liu, Tangjie Lyu, Changjie Fan |
| 2024 | Xinyu: An Efficient LLM-based System for Commentary Generation. Yiquan Wu, Bo Tang, Chenyang Xi, Yu Yu, Pengyu Wang, Yifei Liu, Kun Kuang, Haiying Deng, Zhiyu Li, Feiyu Xiong, Jie Hu, Peng Cheng, Zhonghao Wang, Yi Wang, Yi Luo, Mingchuan Yang |
| 2024 | Your Neighbor Matters: Towards Fair Decisions Under Networked Interference. Wenjing Yang, Haotian Wang, Haoxuan Li, Hao Zou, Ruochun Jin, Kun Kuang, Peng Cui |
| 2024 | ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs. Yuhan Li, Peisong Wang, Zhixun Li, Jeffrey Xu Yu, Jia Li |
| 2024 | epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. Alexander Rodríguez, Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Marie-Laure Charpignon, Kai Wang, Serina Chang, Anil Vullikanti, B. Aditya Prakash |