| 2023 | 19th International Workshop on Mining and Learning with Graphs (MLG). Neil Shah, Shobeir Fakhraei, Da Zheng, Bahare Fatemi, Leman Akoglu |
| 2023 | 22nd International Workshop on Data Mining in Bioinformatics (BIOKDD 2023). Da Yan, Ariful Azad, Jie Hou, Jake Y. Chen, Mohammed J. Zaki |
| 2023 | 2nd Workshop on End-End Customer Journey Optimization. Hongying Zhao, Zhenyu Zhao, Anbang Xu, Neha Gupta, Mert Bay |
| 2023 | 2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen, Jiayu Zhou |
| 2023 | 2nd Workshop on Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond. Chu Wang, Yingfei Wang, Haipeng Luo, Daniel R. Jiang, Jinghai He, Zeyu Zheng |
| 2023 | 2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making. Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Haifeng Chen |
| 2023 | 3D-IDS: Doubly Disentangled Dynamic Intrusion Detection. Chenyang Qiu, Yingsheng Geng, Junrui Lu, Kaida Chen, Shitong Zhu, Ya Su, Guoshun Nan, Can Zhang, Junsong Fu, Qimei Cui, Xiaofeng Tao |
| 2023 | 3D-Polishing for Triangular Mesh Compression of Point Cloud Data. Jiaqi Gu, Guosheng Yin |
| 2023 | 3rd Workshop on Online and Adaptive Recommender Systems (OARS). Xiquan Cui, Vachik S. Dave, Yi Su, Khalifeh Al Jadda, Srijan Kumar, Julian J. McAuley, Tao Ye, Stephen D. Guo, Chip Huyen |
| 2023 | A Causality Inspired Framework for Model Interpretation. Chenwang Wu, Xiting Wang, Defu Lian, Xing Xie, Enhong Chen |
| 2023 | A Collaborative Transfer Learning Framework for Cross-domain Recommendation. Wei Zhang, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang |
| 2023 | A Data-Driven Decision Support Framework for Player Churn Analysis in Online Games. Yu Xiong, Runze Wu, Shiwei Zhao, Jianrong Tao, Xudong Shen, Tangjie Lyu, Changjie Fan, Peng Cui |
| 2023 | A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability. Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du |
| 2023 | A Data-driven Region Generation Framework for Spatiotemporal Transportation Service Management. Liyue Chen, Jiangyi Fang, Zhe Yu, Yongxin Tong, Shaosheng Cao, Leye Wang |
| 2023 | A Dual-Agent Scheduler for Distributed Deep Learning Jobs on Public Cloud via Reinforcement Learning. Mingzhe Xing, Hangyu Mao, Shenglin Yin, Lichen Pan, Zhengchao Zhang, Zhen Xiao, Jieyi Long |
| 2023 | A Feature-Based Coalition Game Framework with Privileged Knowledge Transfer for User-tag Profile Modeling. Xianghui Zhu, Peng Du, Shuo Shao, Chenxu Zhu, Weinan Zhang, Yang Wang, Yang Cao |
| 2023 | A Higher-Order Temporal H-Index for Evolving Networks. Lutz Oettershagen, Nils M. Kriege, Petra Mutzel |
| 2023 | A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification. Kevin Fauvel, Fuxing Chen, Dario Rossi |
| 2023 | A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection. Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li |
| 2023 | A Message Passing Neural Network Space for Better Capturing Data-dependent Receptive Fields. Zhili Wang, Shimin Di, Lei Chen |
| 2023 | A Multi-stage Framework for Online Bonus Allocation Based on Constrained User Intent Detection. Chao Wang, Xiaowei Shi, Shuai Xu, Zhe Wang, Zhiqiang Fan, Yan Feng, An You, Yu Chen |
| 2023 | A Personalized Automated Bidding Framework for Fairness-aware Online Advertising. Haoqi Zhang, Lvyin Niu, Zhenzhe Zheng, Zhilin Zhang, Shan Gu, Fan Wu, Chuan Yu, Jian Xu, Guihai Chen, Bo Zheng |
| 2023 | A Predict-Then-Optimize Couriers Allocation Framework for Emergency Last-mile Logistics. Kaiwen Xia, Li Lin, Shuai Wang, Haotian Wang, Desheng Zhang, Tian He |
| 2023 | A Preference-aware Meta-optimization Framework for Personalized Vehicle Energy Consumption Estimation. Siqi Lai, Weijia Zhang, Hao Liu |
| 2023 | A Sequence-to-Sequence Approach with Mixed Pointers to Topic Segmentation and Segment Labeling. Jinxiong Xia, Houfeng Wang |
| 2023 | A Study of Situational Reasoning for Traffic Understanding. Jiarui Zhang, Filip Ilievski, Kaixin Ma, Aravinda Kollaa, Jonathan Francis, Alessandro Oltramari |
| 2023 | A Sublinear Time Algorithm for Opinion Optimization in Directed Social Networks via Edge Recommendation. Xiaotian Zhou, Liwang Zhu, Wei Li, Zhongzhi Zhang |
| 2023 | A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang |
| 2023 | AI Explainability 360 Toolkit for Time-Series and Industrial Use Cases. Giridhar Ganapavarapu, Sumanta Mukherjee, Natalia Martinez Gil, Kanthi K. Sarpatwar, Amaresh Rajasekharan, Amit Dhurandhar, Vijay Arya, Roman Vaculín |
| 2023 | Accelerating Antimicrobial Peptide Discovery with Latent Structure. Danqing Wang, Zeyu Wen, Fei Ye, Lei Li, Hao Zhou |
| 2023 | Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds. Haoran Deng, Yang Yang, Jiahe Li, Haoyang Cai, Shiliang Pu, Weihao Jiang |
| 2023 | Accelerating Personalized PageRank Vector Computation. Zhen Chen, Xingzhi Guo, Baojian Zhou, Deqing Yang, Steven Skiena |
| 2023 | AdKDD 2023. Abraham Bagherjeiran, Nemanja Djuric, Kuang-Chih Lee, Linsey Pang, Vladan Radosavljevic, Suju Rajan |
| 2023 | AdSEE: Investigating the Impact of Image Style Editing on Advertisement Attractiveness. Liyao Jiang, Chenglin Li, Haolan Chen, Xiaodong Gao, Xinwang Zhong, Yang Qiu, Shani Ye, Di Niu |
| 2023 | AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning. Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han |
| 2023 | AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations. Danwei Li, Zhengyu Zhang, Siyang Yuan, Mingze Gao, Weilin Zhang, Chaofei Yang, Xi Liu, Jiyan Yang |
| 2023 | Adaptive Disentangled Transformer for Sequential Recommendation. Yipeng Zhang, Xin Wang, Hong Chen, Wenwu Zhu |
| 2023 | Adaptive Graph Contrastive Learning for Recommendation. Yangqin Jiang, Chao Huang, Lianghao Huang |
| 2023 | Addressing Bias and Fairness in Machine Learning: A Practical Guide and Hands-on Tutorial. Rayid Ghani, Kit T. Rodolfa, Pedro Saleiro, Sérgio M. Jesus |
| 2023 | Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learning. Haozhe Wang, Chao Du, Panyan Fang, Li He, Liang Wang, Bo Zheng |
| 2023 | Adversaries with Limited Information in the Friedkin-Johnsen Model. Sijing Tu, Stefan Neumann, Aristides Gionis |
| 2023 | AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedIn. Zhentao Xu, Ruoying Wang, Girish Balaji, Manas Bundele, Xiao-Fei Liu, Leo Liu, Tie Wang |
| 2023 | All in One: Multi-Task Prompting for Graph Neural Networks. Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan |
| 2023 | An Empirical Study of Selection Bias in Pinterest Ads Retrieval. Yuan Wang, Peifeng Yin, Zhiqiang Tao, Hari Venkatesan, Jin Lai, Yi Fang, PJ Xiao |
| 2023 | An Interpretable, Flexible, and Interactive Probabilistic Framework for Melody Generation. Stephen Hahn, Rico Zhu, Simon Mak, Cynthia Rudin, Yue Jiang |
| 2023 | An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series. Xu Wang, Hongbo Zhang, Pengkun Wang, Yudong Zhang, Binwu Wang, Zhengyang Zhou, Yang Wang |
| 2023 | Analysis of COVID-19 Offensive Tweets and Their Targets. Song Liao, Ebuka Okpala, Long Cheng, Mingqi Li, Nishant Vishwamitra, Hongxin Hu, Feng Luo, Matthew Costello |
| 2023 | Anomaly Detection with Score Distribution Discrimination. Minqi Jiang, Songqiao Han, Hailiang Huang |
| 2023 | Approximation Algorithms for Size-Constrained Non-Monotone Submodular Maximization in Deterministic Linear Time. Yixin Chen, Alan Kuhnle |
| 2023 | Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent Representation. Bing Xue, Ahmed Sameh Said, Ziqi Xu, Hanyang Liu, Neel Shah, Hanqing Yang, Philip R. O. Payne, Chenyang Lu |
| 2023 | Augmenting Recurrent Graph Neural Networks with a Cache. Guixiang Ma, Vy A. Vo, Theodore L. Willke, Nesreen K. Ahmed |
| 2023 | Augmenting Rule-based DNS Censorship Detection at Scale with Machine Learning. Jacob Alexander Markson Brown, Xi Jiang, Van Hong Tran, Arjun Nitin Bhagoji, Nguyen Phong Hoang, Nick Feamster, Prateek Mittal, Vinod Yegneswaran |
| 2023 | Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines. Dezhan Tu, Yeye He, Weiwei Cui, Song Ge, Haidong Zhang, Shi Han, Dongmei Zhang, Surajit Chaudhuri |
| 2023 | Automated 3D Pre-Training for Molecular Property Prediction. Xu Wang, Huan Zhao, Wei-Wei Tu, Quanming Yao |
| 2023 | Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai |
| 2023 | Automatic Temporal Relation in Multi-Task Learning. Menghui Zhou, Po Yang |
| 2023 | B Mengyue Liu, Yun Lin, Jun Liu, Bohao Liu, Qinghua Zheng, Jin Song Dong |
| 2023 | BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction. Dong Wang, Kavé Salamatian, Yunqing Xia, Weiwei Deng, Qi Zhang |
| 2023 | BOSS: A Bilateral Occupational-Suitability-Aware Recommender System for Online Recruitment. Xiao Hu, Yuan Cheng, Zhi Zheng, Yue Wang, Xinxin Chi, Hengshu Zhu |
| 2023 | Balancing Approach for Causal Inference at Scale. Sicheng Lin, Meng Xu, Xi Zhang, Shih-Kang Chao, Ying-Kai Huang, Xiaolin Shi |
| 2023 | Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM. Hyunsung Kim, Han-Jun Choi, Changjo Kim, Jinsung Yoon, Sang-Ki Ko |
| 2023 | BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs. Zhen Yang, Tinglin Huang, Ming Ding, Yuxiao Dong, Rex Ying, Yukuo Cen, Yangliao Geng, Jie Tang |
| 2023 | Below the Surface: Summarizing Event Sequences with Generalized Sequential Patterns. Joscha Cüppers, Jilles Vreeken |
| 2023 | Binary Classifier Evaluation on Unlabeled Segments using Inverse Distance Weighting with Distance Learning. Xu Chen, Katerina Marazopoulou, Wesley Lee, Christine Agarwal, Jason Sukumaran, Aude Hofleitner |
| 2023 | Binary Embedding-based Retrieval at Tencent. Yukang Gan, Yixiao Ge, Chang Zhou, Shupeng Su, Zhouchuan Xu, Xuyuan Xu, Quanchao Hui, Xiang Chen, Yexin Wang, Ying Shan |
| 2023 | Boosting Multitask Learning on Graphs through Higher-Order Task Affinities. Dongyue Li, Haotian Ju, Aneesh Sharma, Hongyang R. Zhang |
| 2023 | C-AOI: Contour-based Instance Segmentation for High-Quality Areas-of-Interest in Online Food Delivery Platform. Yida Zhu, Liying Chen, Daping Xiong, Shuiping Chen, Fangxiao Du, Jinghua Hao, Renqing He, Zhizhao Sun |
| 2023 | CADENCE: Offline Category Constrained and Diverse Query Generation for E-commerce Autosuggest. Abhinav Anand, Surender Kumar, Nandeesh Kumar, Samir Shah |
| 2023 | CARL-G: Clustering-Accelerated Representation Learning on Graphs. William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis |
| 2023 | CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic Simulation. Chumeng Liang, Zherui Huang, Yicheng Liu, Zhanyu Liu, Guanjie Zheng, Hanyuan Shi, Kan Wu, Yuhao Du, Fuliang Li, Zhenhui Jessie Li |
| 2023 | CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems. Song Jiang, Zijie Huang, Xiao Luo, Yizhou Sun |
| 2023 | CFGL-LCR: A Counterfactual Graph Learning Framework for Legal Case Retrieval. Kun Zhang, Chong Chen, Yuanzhuo Wang, Qi Tian, Long Bai |
| 2023 | CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning. Jianfeng He, Xuchao Zhang, Shuo Lei, Abdulaziz Alhamadani, Fanglan Chen, Bei Xiao, Chang-Tien Lu |
| 2023 | COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search. Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder |
| 2023 | CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation. Chong Liu, Xiaoyang Liu, Rongqin Zheng, Lixin Zhang, Xiaobo Liang, Juntao Li, Lijun Wu, Min Zhang, Leyu Lin |
| 2023 | CampER: An Effective Framework for Privacy-Aware Deep Entity Resolution. Yuxiang Guo, Lu Chen, Zhengjie Zhou, Baihua Zheng, Ziquan Fang, Zhikun Zhang, Yuren Mao, Yunjun Gao |
| 2023 | Capacity Constrained Influence Maximization in Social Networks. Shiqi Zhang, Yiqian Huang, Jiachen Sun, Wenqing Lin, Xiaokui Xiao, Bo Tang |
| 2023 | Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach. Zhangming Chan, Yu Zhang, Shuguang Han, Yong Bai, Xiang-Rong Sheng, Siyuan Lou, Jiacen Hu, Baolin Liu, Yuning Jiang, Jian Xu, Bo Zheng |
| 2023 | Causal Discovery from Temporal Data. Chang Gong, Di Yao, Chuzhe Zhang, Wenbin Li, Jingping Bi, Lun Du, Jin Wang |
| 2023 | Causal Effect Estimation on Hierarchical Spatial Graph Data. Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi |
| 2023 | Causal Inference and Machine Learning in Practice: Use Cases for Product, Brand, Policy and Beyond. Jeong-Yoon Lee, Yifeng Wu, Keith Battocchi, Fabio Vera, Zhenyu Zhao, Totte Harinen, Jing Pan, Huigang Chen, Zeyu Zheng, Chu Wang, Yingfei Wang, Xinwei Ma |
| 2023 | Causal Inference via Style Transfer for Out-of-distribution Generalisation. Toan Nguyen, Kien Do, Duc Thanh Nguyen, Bao Duong, Thin Nguyen |
| 2023 | Certified Edge Unlearning for Graph Neural Networks. Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang |
| 2023 | Classification of Edge-dependent Labels of Nodes in Hypergraphs. Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin |
| 2023 | Clenshaw Graph Neural Networks. Yuhe Guo, Zhewei Wei |
| 2023 | CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X. Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Lei Shen, Zihan Wang, Andi Wang, Yang Li, Teng Su, Zhilin Yang, Jie Tang |
| 2023 | Cognitive Evolutionary Search to Select Feature Interactions for Click-Through Rate Prediction. Runlong Yu, Xiang Xu, Yuyang Ye, Qi Liu, Enhong Chen |
| 2023 | Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay. Xiaoling Zang, Binbin Hu, Jun Chu, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong |
| 2023 | Communication Efficient Distributed Newton Method with Fast Convergence Rates. Chengchang Liu, Lesi Chen, Luo Luo, John C. S. Lui |
| 2023 | Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting. Ergute Bao, Dawei Gao, Xiaokui Xiao, Yaliang Li |
| 2023 | Community-based Dynamic Graph Learning for Popularity Prediction. Shuo Ji, Xiaodong Lu, Mingzhe Liu, Leilei Sun, Chuanren Liu, Bowen Du, Hui Xiong |
| 2023 | Complementary Classifier Induced Partial Label Learning. Yuheng Jia, Chongjie Si, Min-Ling Zhang |
| 2023 | Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19. Ting Dang, Jing Han, Tong Xia, Erika Bondareva, Chloë Siegele-Brown, Jagmohan Chauhan, Andreas Grammenos, Dimitris Spathis, Pietro Cicuta, Cecilia Mascolo |
| 2023 | Connecting the Dots - Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering. Anna Beer, Andrew Draganov, Ellen Hohma, Philipp Jahn, Christian M. M. Frey, Ira Assent |
| 2023 | Constrained Social Community Recommendation. Xingyi Zhang, Shuliang Xu, Wenqing Lin, Sibo Wang |
| 2023 | Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference. Junyan Li, Li Lyna Zhang, Jiahang Xu, Yujing Wang, Shaoguang Yan, Yunqing Xia, Yuqing Yang, Ting Cao, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang |
| 2023 | Context-aware Event Forecasting via Graph Disentanglement. Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua |
| 2023 | Contextual Self-attentive Temporal Point Process for Physical Decommissioning Prediction of Cloud Assets. Fangkai Yang, Jue Zhang, Lu Wang, Bo Qiao, Di Weng, Xiaoting Qin, Gregory Weber, Durgesh Nandini Das, Srinivasan Rakhunathan, Ranganathan Srikanth, Qingwei Lin, Dongmei Zhang |
| 2023 | Contrastive Cross-scale Graph Knowledge Synergy. Yifei Zhang, Yankai Chen, Zixing Song, Irwin King |
| 2023 | Contrastive Learning for User Sequence Representation in Personalized Product Search. Shitong Dai, Jiongnan Liu, Zhicheng Dou, Haonan Wang, Lin Liu, Bo Long, Ji-Rong Wen |
| 2023 | Contrastive Learning of Stress-specific Word Embedding for Social Media based Stress Detection. Xin Wang, Huijun Zhang, Lei Cao, Kaisheng Zeng, Qi Li, Ningyun Li, Ling Feng |
| 2023 | Contrastive Meta-Learning for Few-shot Node Classification. Song Wang, Zhen Tan, Huan Liu, Jundong Li |
| 2023 | Controllable Multi-Objective Re-ranking with Policy Hypernetworks. Sirui Chen, Yuan Wang, Zijing Wen, Zhiyu Li, Changshuo Zhang, Xiao Zhang, Quan Lin, Cheng Zhu, Jun Xu |
| 2023 | CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations. Hangzhi Guo, Thanh Hong Nguyen, Amulya Yadav |
| 2023 | Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation. Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang |
| 2023 | Counterfactual Video Recommendation for Duration Debiasing. Shisong Tang, Qing Li, Dingmin Wang, Ci Gao, Wentao Xiao, Dan Zhao, Yong Jiang, Qian Ma, Aoyang Zhang |
| 2023 | Cracking White-box DNN Watermarks via Invariant Neuron Transforms. Xudong Pan, Mi Zhang, Yifan Yan, Yining Wang, Min Yang |
| 2023 | Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation. Jin-Duk Park, Siqing Li, Xin Cao, Won-Yong Shin |
| 2023 | CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning. Gang Yan, Hao Wang, Xu Yuan, Jian Li |
| 2023 | DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun |
| 2023 | DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection. Jiaying Wu, Bryan Hooi |
| 2023 | DGI: An Easy and Efficient Framework for GNN Model Evaluation. Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang |
| 2023 | DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization. Wenhao Zhang, Zimu Zhou, Yansheng Wang, Yongxin Tong |
| 2023 | DNet: Distributional Network for Distributional Individualized Treatment Effects. Guojun Wu, Ge Song, Xiaoxiang Lv, Shikai Luo, Chengchun Shi, Hongtu Zhu |
| 2023 | DRL4Route: A Deep Reinforcement Learning Framework for Pick-up and Delivery Route Prediction. Xiaowei Mao, Haomin Wen, Hengrui Zhang, Huaiyu Wan, Lixia Wu, Jianbin Zheng, Haoyuan Hu, Youfang Lin |
| 2023 | Data-Efficient and Interpretable Tabular Anomaly Detection. Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister |
| 2023 | Data-centric AI: Techniques and Future Perspectives. Daochen Zha, Kwei-Herng Lai, Fan Yang, Na Zou, Huiji Gao, Xia Hu |
| 2023 | Debiasing Recommendation by Learning Identifiable Latent Confounders. Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo |
| 2023 | Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning. Deniz Koyuncu, Alex Gittens, Bülent Yener, Moti Yung |
| 2023 | Decoupled Rationalization with Asymmetric Learning Rates: A Flexible Lipschitz Restraint. Wei Liu, Jun Wang, Haozhao Wang, Ruixuan Li, Yang Qiu, Yuankai Zhang, Jie Han, Yixiong Zou |
| 2023 | Deep Bayesian Active Learning for Accelerating Stochastic Simulation. Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu |
| 2023 | Deep Encoders with Auxiliary Parameters for Extreme Classification. Kunal Dahiya, Sachin Yadav, Sushant Sondhi, Deepak Saini, Sonu Mehta, Jian Jiao, Sumeet Agarwal, Purushottam Kar, Manik Varma |
| 2023 | Deep Landscape Forecasting in Multi-Slot Real-Time Bidding. Weitong Ou, Bo Chen, Yingxuan Yang, Xinyi Dai, Weiwen Liu, Weinan Zhang, Ruiming Tang, Yong Yu |
| 2023 | Deep Learning on Graphs: Methods and Applications (DLG-KDD2023). Lingfei Wu, Jian Pei, Jiliang Tang, Yinglong Xia, Xiaojie Guo |
| 2023 | Deep Offline Reinforcement Learning for Real-world Treatment Optimization Applications. Mila Nambiar, Supriyo Ghosh, Priscilla Ong, Yu En Chan, Yong Mong Bee, Pavitra Krishnaswamy |
| 2023 | Deep Pipeline Embeddings for AutoML. Sebastian Pineda-Arango, Josif Grabocka |
| 2023 | Deep Transfer Learning for City-scale Cellular Traffic Generation through Urban Knowledge Graph. Shiyuan Zhang, Tong Li, Shuodi Hui, Guangyu Li, Yanping Liang, Li Yu, Depeng Jin, Yong Li |
| 2023 | Deep Weakly-supervised Anomaly Detection. Guansong Pang, Chunhua Shen, Huidong Jin, Anton van den Hengel |
| 2023 | Delving into Global Dialogue Structures: Structure Planning Augmented Response Selection for Multi-turn Conversations. Tingchen Fu, Xueliang Zhao, Rui Yan |
| 2023 | Demystifying Fraudulent Transactions and Illicit Nodes in the Bitcoin Network for Financial Forensics. Youssef Elmougy, Ling Liu |
| 2023 | Dense Representation Learning and Retrieval for Tabular Data Prediction. Lei Zheng, Ning Li, Xianyu Chen, Quan Gan, Weinan Zhang |
| 2023 | Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity. Atsushi Miyauchi, Tianyi Chen, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis |
| 2023 | Dependence and Model Selection in LLP: The Problem of Variants. Gabriel Franco, Mark Crovella, Giovanni Comarela |
| 2023 | Detecting Interference in Online Controlled Experiments with Increasing Allocation. Kevin Han, Shuangning Li, Jialiang Mao, Han Wu |
| 2023 | Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network. Jinzhu Mao, Liu Cao, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, Yong Li |
| 2023 | Diga: Guided Diffusion Model for Graph Recovery in Anti-Money Laundering. Xujia Li, Yuan Li, Xueying Mo, Hebing Xiao, Yanyan Shen, Lei Chen |
| 2023 | DisasterNet: Causal Bayesian Networks with Normalizing Flows for Cascading Hazards Estimation from Satellite Imagery. Xuechun Li, Paula M. Bürgi, Wei Ma, Hae Young Noh, David Jay Wald, Susu Xu |
| 2023 | Discovering Dynamic Causal Space for DAG Structure Learning. Fangfu Liu, Wenchang Ma, An Zhang, Xiang Wang, Yueqi Duan, Tat-Seng Chua |
| 2023 | Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks. Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C. Uyeda, Meghan A. Balk, Wasila M. Dahdul, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V. Stewart, Daniel I. Rubenstein, Tanya Y. Berger-Wolf, Anuj Karpatne |
| 2023 | Distributed Optimization for Big Data Analytics: Beyond Minimization. Hongchang Gao, Xinwen Zhang |
| 2023 | Doctor Specific Tag Recommendation for Online Medical Record Management. Yejing Wang, Shen Ge, Xiangyu Zhao, Xian Wu, Tong Xu, Chen Ma, Zhi Zheng |
| 2023 | Domain-Guided Spatio-Temporal Self-Attention for Egocentric 3D Pose Estimation. Jinman Park, Kimathi Kaai, Saad Hossain, Norikatsu Sumi, Sirisha Rambhatla, Paul W. Fieguth |
| 2023 | Domain-Specific Risk Minimization for Domain Generalization. Yifan Zhang, Jindong Wang, Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, Dacheng Tao, Xing Xie |
| 2023 | DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication. Igor Nunes, Mike Heddes, Pere Vergés, Danny Abraham, Alexander V. Veidenbaum, Alex Nicolau, Tony Givargis |
| 2023 | DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting. Lifan Zhao, Shuming Kong, Yanyan Shen |
| 2023 | Doubly Robust AUC Optimization against Noisy and Adversarial Samples. Chenkang Zhang, Wanli Shi, Lei Luo, Bin Gu |
| 2023 | Dual-view Molecular Pre-training. Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Wengang Zhou, Tao Qin, Houqiang Li, Tie-Yan Liu |
| 2023 | DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling. Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang |
| 2023 | DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph. Kaike Zhang, Qi Cao, Gaolin Fang, Bingbing Xu, Hongjian Zou, Huawei Shen, Xueqi Cheng |
| 2023 | E-commerce Search via Content Collaborative Graph Neural Network. Guipeng Xv, Chen Lin, Wanxian Guan, Jinping Gou, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng |
| 2023 | ECGGAN: A Framework for Effective and Interpretable Electrocardiogram Anomaly Detection. Huazhang Wang, Zhaojing Luo, James Wei Luen Yip, Chuyang Ye, Meihui Zhang |
| 2023 | ESSA: Explanation Iterative Supervision via Saliency-guided Data Augmentation. Siyi Gu, Yifei Zhang, Yuyang Gao, Xiaofeng Yang, Liang Zhao |
| 2023 | EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation. Kuo Yang, Zhengyang Zhou, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang |
| 2023 | Efficient Approximation Algorithms for Spanning Centrality. Shiqi Zhang, Renchi Yang, Jing Tang, Xiaokui Xiao, Bo Tang |
| 2023 | Efficient Bi-Level Optimization for Recommendation Denoising. Zongwei Wang, Min Gao, Wentao Li, Junliang Yu, Linxin Guo, Hongzhi Yin |
| 2023 | Efficient Centrality Maximization with Rademacher Averages. Leonardo Pellegrina |
| 2023 | Efficient Continuous Space Policy Optimization for High-frequency Trading. Li Han, Nan Ding, Guoxuan Wang, Dawei Cheng, Yuqi Liang |
| 2023 | Efficient Coreset Selection with Cluster-based Methods. Chengliang Chai, Jiayi Wang, Nan Tang, Ye Yuan, Jiabin Liu, Yuhao Deng, Guoren Wang |
| 2023 | Efficient Distributed Approximate k-Nearest Neighbor Graph Construction by Multiway Random Division Forest. Sang-Hong Kim, Ha-Myung Park |
| 2023 | Efficient Single-Source SimRank Query by Path Aggregation. Mingxi Zhang, Yanghua Xiao, Wei Wang |
| 2023 | Efficient Sparse Linear Bandits under High Dimensional Data. Xue Wang, Mike Mingcheng Wei, Tao Yao |
| 2023 | Efficient and Effective Edge-wise Graph Representation Learning. Hewen Wang, Renchi Yang, Keke Huang, Xiaokui Xiao |
| 2023 | Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering. Yan Wen, Chen Gao, Lingling Yi, Liwei Qiu, Yaqing Wang, Yong Li |
| 2023 | Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective. Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng |
| 2023 | Empowering General-purpose User Representation with Full-life Cycle Behavior Modeling. Bei Yang, Jie Gu, Ke Liu, Xiaoxiao Xu, Renjun Xu, Qinghui Sun, Hong Liu |
| 2023 | Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi |
| 2023 | End-to-End Inventory Prediction and Contract Allocation for Guaranteed Delivery Advertising. Wuyang Mao, Chuanren Liu, Yundu Huang, Zhonglin Zu, M. Harshvardhan, Liang Wang, Bo Zheng |
| 2023 | End-to-End Query Term Weighting. Karan Samel, Cheng Li, Weize Kong, Tao Chen, Mingyang Zhang, Shaleen Kumar Gupta, Swaraj Khadanga, Wensong Xu, Xingyu Wang, Kashyap Kolipaka, Michael Bendersky, Marc Najork |
| 2023 | Enhance Diffusion to Improve Robust Generalization. Jianhui Sun, Sanchit Sinha, Aidong Zhang |
| 2023 | Enhancing Graph Representations Learning with Decorrelated Propagation. Hua Liu, Haoyu Han, Wei Jin, Xiaorui Liu, Hui Liu |
| 2023 | Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks. Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin |
| 2023 | Entity-aware Multi-task Learning for Query Understanding at Walmart. Zhiyuan Peng, Vachik S. Dave, Nicole McNabb, Rahul Sharnagat, Alessandro Magnani, Ciya Liao, Yi Fang, Sravanthi Rajanala |
| 2023 | EvalRS 2023: Well-Rounded Recommender Systems for Real-World Deployments. Federico Bianchi, Patrick John Chia, Jacopo Tagliabue, Ciro Greco, Gabriel de Souza P. Moreira, Davide Eynard, Fahd Husain, Claudio Pomo |
| 2023 | Evolve Path Tracer: Early Detection of Malicious Addresses in Cryptocurrency. Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu |
| 2023 | Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song |
| 2023 | Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering. Xinyue Hu, Lin Gu, Qiyuan An, Mengliang ZHang, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu |
| 2023 | ExplainableFold: Understanding AlphaFold Prediction with Explainable AI. Juntao Tan, Yongfeng Zhang |
| 2023 | Explicit Feature Interaction-aware Uplift Network for Online Marketing. Dugang Liu, Xing Tang, Han Gao, Fuyuan Lyu, Xiuqiang He |
| 2023 | Exploiting Intent Evolution in E-commercial Query Recommendation. Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Xiao Cheng, Bing Yin, Suhang Wang, Philip S. Yu |
| 2023 | Exploiting Relation-aware Attribute Representation Learning in Knowledge Graph Embedding for Numerical Reasoning. Gayeong Kim, Sookyung Kim, Ko Keun Kim, Suchan Park, Heesoo Jung, Hogun Park |
| 2023 | Extreme Multi-Label Classification for Ad Targeting using Factorization Machines. Martin Pavlovski, Srinath Ravindran, Djordje Gligorijevic, Shubham Agrawal, Ivan Stojkovic, Nelson Segura-Nunez, Jelena Gligorijevic |
| 2023 | FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework. Raneen Younis, Zahra Ahmadi, Abdul Hakmeh, Marco Fisichella |
| 2023 | FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs. Yang Liu, Xiang Ao, Fuli Feng, Yunshan Ma, Kuan Li, Tat-Seng Chua, Qing He |
| 2023 | FS-REAL: Towards Real-World Cross-Device Federated Learning. Daoyuan Chen, Dawei Gao, Yuexiang Xie, Xuchen Pan, Zitao Li, Yaliang Li, Bolin Ding, Jingren Zhou |
| 2023 | Fair Allocation Over Time, with Applications to Content Moderation. Amine Allouah, Christian Kroer, Xuan Zhang, Vashist Avadhanula, Nona Bohanon, Anil Dania, Caner Gocmen, Sergey Pupyrev, Parikshit Shah, Nicolás Stier Moses, Ken Rodríguez Taarup |
| 2023 | Fair Multilingual Vandalism Detection System for Wikipedia. Mykola Trokhymovych, Muniza Aslam, Ai-Jou Chou, Ricardo Baeza-Yates, Diego Sáez-Trumper |
| 2023 | FairCod: A Fairness-aware Concurrent Dispatch System for Large-scale Instant Delivery Services. Lin Jiang, Shuai Wang, Baoshen Guo, Hai Wang, Desheng Zhang, Guang Wang |
| 2023 | Fairness in Graph Machine Learning: Recent Advances and Future Prospectives. Yushun Dong, Oyku Deniz Kose, Yanning Shen, Jundong Li |
| 2023 | Fairness-Aware Continuous Predictions of Multiple Analytics Targets in Dynamic Networks. Ruifeng Liu, Qu Liu, Tingjian Ge |
| 2023 | Fast Text Generation with Text-Editing Models. Eric Malmi, Yue Dong, Jonathan Mallinson, Aleksandr Chuklin, Jakub Adámek, Daniil Mirylenka, Felix Stahlberg, Sebastian Krause, Shankar Kumar, Aliaksei Severyn |
| 2023 | Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors - Algorithm and Application. Jun-Gi Jang, Jeongyoung Lee, Yong-chan Park, U Kang |
| 2023 | Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations. Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin V. Bonilla, Gholamreza Haffari, Dinh Q. Phung |
| 2023 | FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity. Zhen Qin, Shuiguang Deng, Mingyu Zhao, Xueqiang Yan |
| 2023 | FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy. Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan |
| 2023 | FedDefender: Client-Side Attack-Tolerant Federated Learning. Sungwon Park, Sungwon Han, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha |
| 2023 | FedMultimodal: A Benchmark for Multimodal Federated Learning. Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan |
| 2023 | FedPseudo: Privacy-Preserving Pseudo Value-Based Deep Learning Models for Federated Survival Analysis. Md. Mahmudur Rahman, Sanjay Purushotham |
| 2023 | FedSkill: Privacy Preserved Interpretable Skill Learning via Imitation. Yushan Jiang, Wenchao Yu, Dongjin Song, Lu Wang, Wei Cheng, Haifeng Chen |
| 2023 | Federated Few-shot Learning. Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li |
| 2023 | Few-shot Low-resource Knowledge Graph Completion with Multi-view Task Representation Generation. Shichao Pei, Ziyi Kou, Qiannan Zhang, Xiangliang Zhang |
| 2023 | Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning. Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou |
| 2023 | Finding Favourite Tuples on Data Streams with Provably Few Comparisons. Guangyi Zhang, Nikolaj Tatti, Aristides Gionis |
| 2023 | Fire: An Optimization Approach for Fast Interpretable Rule Extraction. Brian Liu, Rahul Mazumder |
| 2023 | Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. Derek Zhiyuan Cheng, Dhaval Patel, Linsey Pang, Sameep Mehta, Kexin Xie, Ed H. Chi, Wei Liu, Nitesh V. Chawla, James Bailey |
| 2023 | Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond. Naoki Abe, Kathleen Buckingham, Yuzhou Chen, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, Yulia R. Gel, James Hodson, Ramakrishnan Kannan, Huikyo Lee, Jiafu Mao, Rose Yu |
| 2023 | Fragility Index: A New Approach for Binary Classification. Chen Yang, Ziqiang Zhang, Bo Cao, Zheng Cui, Bin Hu, Tong Li, Daniel Zhuoyu Long, Jin Qi, Feng Wang, Ruohan Zhan |
| 2023 | Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos J. Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen |
| 2023 | Frigate: Frugal Spatio-temporal Forecasting on Road Networks. Mridul Gupta, Hariprasad Kodamana, Sayan Ranu |
| 2023 | From Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams. Iddo Drori, Sarah J. Zhang, Reece Shuttleworth, Sarah Zhang, Keith Tyser, Zad Chin, Pedro Lantigua, Saisamrit Surbehera, Gregory Hunter, Derek Austin, Leonard Tang, Yann Hicke, Sage Simhon, Sathwik Karnik, Darnell Granberry, Madeleine Udell |
| 2023 | From Innovation to Scale (I2S) - Discuss and Learn How to Successfully Build, Commercialize, and Scale AI Innovations in Challenging Market Conditions. Ankur Teredesai, Michael Zeller, Shenghua Bao, Wee Hyong Tok, Linsey Pang |
| 2023 | From Labels to Decisions: A Mapping-Aware Annotator Model. Evan Yao, Jagdish Ramakrishnan, Xu Chen, Viet-An Nguyen, Udi Weinsberg |
| 2023 | Fusing Multimodal Signals on Hyper-complex Space for Extreme Abstractive Text Summarization (TL;DR) of Scientific Contents. Yash Kumar Atri, Vikram Goyal, Tanmoy Chakraborty |
| 2023 | GAL-VNE: Solving the VNE Problem with Global Reinforcement Learning and Local One-Shot Neural Prediction. Haoyu Geng, Runzhong Wang, Fei Wu, Junchi Yan |
| 2023 | GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning. Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan, Yong Li |
| 2023 | GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation. Jing Zhang, Xiaokang Zhang, Daniel Zhang-Li, Jifan Yu, Zijun Yao, Zeyao Ma, Yiqi Xu, Haohua Wang, Xiaohan Zhang, Nianyi Lin, Sunrui Lu, Juanzi Li, Jie Tang |
| 2023 | GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing. Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu |
| 2023 | Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning. Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen |
| 2023 | Generalized Matrix Local Low Rank Representation by Random Projection and Submatrix Propagation. Pengtao Dang, Haiqi Zhu, Tingbo Guo, Changlin Wan, Tong Zhao, Paul Salama, Yijie Wang, Sha Cao, Chi Zhang |
| 2023 | Generalizing Graph ODE for Learning Complex System Dynamics across Environments. Zijie Huang, Yizhou Sun, Wei Wang |
| 2023 | Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning. Shuo Yu, Hongyan Xue, Xiang Ao, Feiyang Pan, Jia He, Dandan Tu, Qing He |
| 2023 | Generative AI meets Responsible AI: Practical Challenges and Opportunities. Krishnaram Kenthapadi, Himabindu Lakkaraju, Nazneen Rajani |
| 2023 | Generative Causal Interpretation Model for Spatio-Temporal Representation Learning. Yu Zhao, Pan Deng, Junting Liu, Xiaofeng Jia, Jianwei Zhang |
| 2023 | Generative Flow Network for Listwise Recommendation. Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian J. McAuley, Dong Zheng, Peng Jiang, Kun Gai |
| 2023 | Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution. Tsuyoshi Idé, Naoki Abe |
| 2023 | GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network. Ran Jia, Haoming Guo, Xiaoyuan Jin, Chao Yan, Lun Du, Xiaojun Ma, Tamara Stankovic, Marko Lozajic, Goran Zoranovic, Igor Ilic, Shi Han, Dongmei Zhang |
| 2023 | Getting an h-Index of 100 in 20 Years or Less! Eamonn J. Keogh |
| 2023 | Grace: Graph Self-Distillation and Completion to Mitigate Degree-Related Biases. Hui Xu, Liyao Xiang, Femke Huang, Yuting Weng, Ruijie Xu, Xinbing Wang, Chenghu Zhou |
| 2023 | Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes Processes. Song Wei, Yao Xie, Christopher S. Josef, Rishikesan Kamaleswaran |
| 2023 | Graph Contrastive Learning with Generative Adversarial Network. Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai |
| 2023 | Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems. Yeping Hu, Bo Lei, Victor M. Castillo |
| 2023 | Graph Neural Bandits. Yunzhe Qi, Yikun Ban, Jingrui He |
| 2023 | Graph Neural Networks in TensorFlow. Bryan Perozzi, Sami Abu-El-Haija, Anton Tsitsulin |
| 2023 | Graph Neural Networks: Foundation, Frontiers and Applications. Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo |
| 2023 | Graph Neural Processes for Spatio-Temporal Extrapolation. Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann |
| 2023 | Graph and Geometry Generative Modeling for Drug Discovery. Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon |
| 2023 | Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications. Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi |
| 2023 | Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems. Xiaohui Chen, Jiankai Sun, Taiqing Wang, Ruocheng Guo, Li-Ping Liu, Aonan Zhang |
| 2023 | GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks. Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan |
| 2023 | GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification. Wen-Zhi Li, Chang-Dong Wang, Hui Xiong, Jian-Huang Lai |
| 2023 | GraphStorm an Easy-to-use and Scalable Graph Neural Network Framework: From Beginners to Heroes. Jian Zhang, Da Zheng, Xiang Song, Theodore Vasiloudis, Israt Nisa, Jim Lu |
| 2023 | Group-based Fraud Detection Network on e-Commerce Platforms. Jianke Yu, Hanchen Wang, Xiaoyang Wang, Zhao Li, Lu Qin, Wenjie Zhang, Jian Liao, Ying Zhang |
| 2023 | Guiding Mathematical Reasoning via Mastering Commonsense Formula Knowledge. Jiayu Liu, Zhenya Huang, Zhiyuan Ma, Qi Liu, Enhong Chen, Tianhuang Su, Haifeng Liu |
| 2023 | HUGE: Huge Unsupervised Graph Embeddings with TPUs. Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi |
| 2023 | Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls". Mia C. Mayer, Muhammad Bilal Zafar, Luca Franceschi, Huzefa Rangwala |
| 2023 | HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline. Yang Li, Xinyan Chen, Wenxuan Guo, Xijun Li, Wanqian Luo, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Junchi Yan |
| 2023 | Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks. Bowen Jin, Yu Zhang, Qi Zhu, Jiawei Han |
| 2023 | HiMacMic: Hierarchical Multi-Agent Deep Reinforcement Learning with Dynamic Asynchronous Macro Strategy. Hancheng Zhang, Guozheng Li, Chi Harold Liu, Guoren Wang, Jian Tang |
| 2023 | Hierarchical Invariant Learning for Domain Generalization Recommendation. Zeyu Zhang, Heyang Gao, Hao Yang, Xu Chen |
| 2023 | Hierarchical Projection Enhanced Multi-behavior Recommendation. Chang Meng, Hengyu Zhang, Wei Guo, Huifeng Guo, Haotian Liu, Yingxue Zhang, Hongkun Zheng, Ruiming Tang, Xiu Li, Rui Zhang |
| 2023 | Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting. Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami |
| 2023 | Hierarchical Reinforcement Learning for Dynamic Autonomous Vehicle Navigation at Intelligent Intersections. Qian Sun, Le Zhang, Huan Yu, Weijia Zhang, Yu Mei, Hui Xiong |
| 2023 | HomoGCL: Rethinking Homophily in Graph Contrastive Learning. Wen-Zhi Li, Chang-Dong Wang, Hui Xiong, Jian-Huang Lai |
| 2023 | How Transitive Are Real-World Group Interactions? - Measurement and Reproduction. Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin |
| 2023 | How does the Memorization of Neural Networks Impact Adversarial Robust Models? Han Xu, Xiaorui Liu, Wentao Wang, Zitao Liu, Anil K. Jain, Jiliang Tang |
| 2023 | How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy. Natalia Ponomareva, Sergei Vassilvitskii, Zheng Xu, Brendan McMahan, Alexey Kurakin, Chiyaun Zhang |
| 2023 | Hyper-USS: Answering Subset Query Over Multi-Attribute Data Stream. Ruijie Miao, Yiyao Zhang, Guanyu Qu, Kaicheng Yang, Tong Yang, Bin Cui |
| 2023 | Hyperbolic Graph Neural Networks: A Tutorial on Methods and Applications. Min Zhou, Menglin Yang, Bo Xiong, Hui Xiong, Irwin King |
| 2023 | Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree. Delvin Ce Zhang, Rex Ying, Hady W. Lauw |
| 2023 | IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics. Jia-Qi Yang, Yucheng Xu, Jia-Lei Shen, Ke-Bin Fan, De-Chuan Zhan, Yang Yang |
| 2023 | IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research. Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-Mei Hwu |
| 2023 | ILRoute: A Graph-based Imitation Learning Method to Unveil Riders' Routing Strategies in Food Delivery Service. Tao Feng, Huan Yan, Huandong Wang, Wenzhen Huang, Yuyang Han, Hongsen Liao, Jinghua Hao, Yong Li |
| 2023 | IPOC: An Adaptive Interval Prediction Model based on Online Chasing and Conformal Inference for Large-Scale Systems. Jiadong Chen, Yang Luo, Xiuqi Huang, Fuxin Jiang, Yangguang Shi, Tieying Zhang, Xiaofeng Gao |
| 2023 | Identifying Complicated Contagion Scenarios from Cascade Data. Galen Harrison, Amro Alabsi Aljundi, Jiangzhuo Chen, S. S. Ravi, Anil Kumar S. Vullikanti, Madhav V. Marathe, Abhijin Adiga |
| 2023 | Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs. Yuankai Luo, Lei Shi, Mufan Xu, Yuwen Ji, Fengli Xiao, Chunming Hu, Zhiguang Shan |
| 2023 | Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay. Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek |
| 2023 | Improving Conversational Recommendation Systems via Counterfactual Data Simulation. Xiaolei Wang, Kun Zhou, Xinyu Tang, Wayne Xin Zhao, Fan Pan, Zhao Cao, Ji-Rong Wen |
| 2023 | Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization. Kaixuan Chen, Shunyu Liu, Tongtian Zhu, Ji Qiao, Yun Su, Yingjie Tian, Tongya Zheng, Haofei Zhang, Zunlei Feng, Jingwen Ye, Mingli Song |
| 2023 | Improving Search Clarification with Structured Information Extracted from Search Results. Ziliang Zhao, Zhicheng Dou, Yu Guo, Zhao Cao, Xiaohua Cheng |
| 2023 | Improving Training Stability for Multitask Ranking Models in Recommender Systems. Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi |
| 2023 | Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information. Tianjun Yao, Yingxu Wang, Kun Zhang, Shangsong Liang |
| 2023 | Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models. Chunjing Xiao, Zehua Gou, Wenxin Tai, Kunpeng Zhang, Fan Zhou |
| 2023 | Incremental Causal Graph Learning for Online Root Cause Analysis. Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, Haifeng Chen |
| 2023 | Influence Maximization with Fairness at Scale. Yuting Feng, Ankitkumar Patel, Bogdan Cautis, Hossein Vahabi |
| 2023 | Interactive Generalized Additive Model and Its Applications in Electric Load Forecasting. Linxiao Yang, Rui Ren, Xinyue Gu, Liang Sun |
| 2023 | Interdependent Causal Networks for Root Cause Localization. Dongjie Wang, Zhengzhang Chen, Jingchao Ni, Liang Tong, Zheng Wang, Yanjie Fu, Haifeng Chen |
| 2023 | Internal Logical Induction for Pixel-Symbolic Reinforcement Learning. Jiacheng Xu, Chao Chen, Fuxiang Zhang, Lei Yuan, Zongzhang Zhang, Yang Yu |
| 2023 | International Workshop on Federated Learning for Distributed Data Mining. Junyuan Hong, Zhuangdi Zhu, Lingjuan Lyu, Yang Zhou, Vishnu Naresh Boddeti, Jiayu Zhou |
| 2023 | International Workshop on Multimodal Learning - 2023 Theme: Multimodal Learning with Foundation Models. Yuan Ling, Fanyou Wu, Shujing Dong, Yarong Feng, George Karypis, Chandan K. Reddy |
| 2023 | Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan |
| 2023 | Investigating Trojan Attacks on Pre-trained Language Model-powered Database Middleware. Peiran Dong, Song Guo, Junxiao Wang |
| 2023 | JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving. Xin Zhao, Kun Zhou, Beichen Zhang, Zheng Gong, Zhipeng Chen, Yuanhang Zhou, Ji-Rong Wen, Jing Sha, Shijin Wang, Cong Liu, Guoping Hu |
| 2023 | Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model. Xiang-Rong Sheng, Jingyue Gao, Yueyao Cheng, Siran Yang, Shuguang Han, Hongbo Deng, Yuning Jiang, Jian Xu, Bo Zheng |
| 2023 | Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs. Zequn Sun, Jiacheng Huang, Jinghao Lin, Xiaozhou Xu, Qijin Chen, Wei Hu |
| 2023 | KDD 2023 International Workshop on Data Science for Social Good (DSSG-23). Amulya Yadav, Aparna Taneja, Ayan Mukhopadhyay, Serina Chang |
| 2023 | KDD 2023 Workshop on Data Science and AI for Sports. Huan Song, Panpan Xu, Lin Lee Cheong, Yuanheng Wang |
| 2023 | KDD Workshop on Machine Learning in Finance. Leman Akoglu, Nitesh V. Chawla, Senthil Kumar, Saurabh Nagrecha, Mahashweta Das, Vidyut M. Naware, Tanveer A. Faruquie |
| 2023 | KDD-2023 Workshop on Decision Intelligence and Analytics for Online Marketplaces. Zhiwei (Tony) Qin, Rui Song, Jieping Ye, Hongtu Zhu, Michael I. Jordan |
| 2023 | Kernel Ridge Regression-Based Graph Dataset Distillation. Zhe Xu, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hao Yang, Hanghang Tong |
| 2023 | KiL 2023 : 3rd International Workshop on Knowledge-infused Learning. Manas Gaur, Efthymia Tsamoura, Sarath Sreedharan, Sudip Mittal |
| 2023 | Knowledge Based Prohibited Item Detection on Heterogeneous Risk Graphs. Tingyan Xiang, Ao Li, Yugang Ji, Dong Li |
| 2023 | Knowledge Graph Reasoning and Its Applications. Lihui Liu, Hanghang Tong |
| 2023 | Knowledge Graph Reasoning over Entities and Numerical Values. Jiaxin Bai, Chen Luo, Zheng Li, Qingyu Yin, Bing Yin, Yangqiu Song |
| 2023 | Knowledge Graph Self-Supervised Rationalization for Recommendation. Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang |
| 2023 | Knowledge-augmented Graph Machine Learning for Drug Discovery: From Precision to Interpretability. Zhiqiang Zhong, Davide Mottin |
| 2023 | LATTE: A Framework for Learning Item-Features to Make a Domain-Expert for Effective Conversational Recommendation. Taeho Kim, Juwon Yu, Won-Yong Shin, Hyunyoung Lee, Ji-Hui Im, Sang-Wook Kim |
| 2023 | LEA: Improving Sentence Similarity Robustness to Typos Using Lexical Attention Bias. Mario Almagro, Emilio J. Almazán, Diego Ortego, David Jiménez |
| 2023 | Large-Scale Graph Neural Networks: The Past and New Frontiers. Rui Xue, Haoyu Han, Tong Zhao, Neil Shah, Jiliang Tang, Xiaorui Liu |
| 2023 | Large-scale Urban Cellular Traffic Generation via Knowledge-Enhanced GANs with Multi-Periodic Patterns. Shuodi Hui, Huandong Wang, Tong Li, Xinghao Yang, Xing Wang, Junlan Feng, Lin Zhu, Chao Deng, Pan Hui, Depeng Jin, Yong Li |
| 2023 | Learning Autoregressive Model in LSM-Tree based Store. Yunxiang Su, Wenxuan Ma, Shaoxu Song |
| 2023 | Learning Balanced Tree Indexes for Large-Scale Vector Retrieval. Wuchao Li, Chao Feng, Defu Lian, Yuxin Xie, Haifeng Liu, Yong Ge, Enhong Chen |
| 2023 | Learning Behavior-oriented Knowledge Tracing. Bihan Xu, Zhenya Huang, Jiayu Liu, Shuanghong Shen, Qi Liu, Enhong Chen, Jinze Wu, Shijin Wang |
| 2023 | Learning Discrete Document Representations in Web Search. Rong Huang, Danfeng Zhang, Weixue Lu, Han Li, Meng Wang, Daiting Shi, Jun Fan, Zhicong Cheng, Simiu Gu, Dawei Yin |
| 2023 | Learning Joint Relational Co-evolution in Spatial-Temporal Knowledge Graph for SMEs Supply Chain Prediction. Youru Li, Zhenfeng Zhu, Xiaobo Guo, Linxun Chen, Zhouyin Wang, Yinmeng Wang, Bing Han, Yao Zhao |
| 2023 | Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance. Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu |
| 2023 | Learning Multivariate Hawkes Process via Graph Recurrent Neural Network. Kanghoon Yoon, Youngjun Im, Jingyu Choi, Taehwan Jeong, Jinkyoo Park |
| 2023 | Learning Slow and Fast System Dynamics via Automatic Separation of Time Scales. Ruikun Li, Huandong Wang, Yong Li |
| 2023 | Learning Strong Graph Neural Networks with Weak Information. Yixin Liu, Kaize Ding, Jianling Wang, Vincent C. S. Lee, Huan Liu, Shirui Pan |
| 2023 | Learning for Counterfactual Fairness from Observational Data. Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li |
| 2023 | Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection. Lorenzo Perini, Vincent Vercruyssen, Jesse Davis |
| 2023 | Learning to Discover Various Simpson's Paradoxes. Jingwei Wang, Jianshan He, Weidi Xu, Ruopeng Li, Wei Chu |
| 2023 | Learning to Relate to Previous Turns in Conversational Search. Fengran Mo, Jian-Yun Nie, Kaiyu Huang, Kelong Mao, Yutao Zhu, Peng Li, Yang Liu |
| 2023 | Learning to Schedule in Diffusion Probabilistic Models. Yunke Wang, Xiyu Wang, Anh-Dung Dinh, Bo Du, Charles Xu |
| 2023 | Learning to Solve Grouped 2D Bin Packing Problems in the Manufacturing Industry. Wenxuan Ao, Guozhen Zhang, Yong Li, Depeng Jin |
| 2023 | Learning-Based Ad Auction Design with Externalities: The Framework and A Matching-Based Approach. Ningyuan Li, Yunxuan Ma, Yang Zhao, Zhijian Duan, Yurong Chen, Zhilin Zhang, Jian Xu, Bo Zheng, Xiaotie Deng |
| 2023 | Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining. Jaemin Yoo, Meng-Chieh Lee, Shubhranshu Shekhar, Christos Faloutsos |
| 2023 | Leveraging Relational Graph Neural Network for Transductive Model Ensemble. Zhengyu Hu, Jieyu Zhang, Haonan Wang, Siwei Liu, Shangsong Liang |
| 2023 | LibAUC: A Deep Learning Library for X-Risk Optimization. Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang |
| 2023 | LightPath: Lightweight and Scalable Path Representation Learning. Sean Bin Yang, Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen |
| 2023 | LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Xiao Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao |
| 2023 | Local Boosting for Weakly-Supervised Learning. Rongzhi Zhang, Yue Yu, Jiaming Shen, Xiquan Cui, Chao Zhang |
| 2023 | Localised Adaptive Spatial-Temporal Graph Neural Network. Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao |
| 2023 | Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing Systems. Peng Peng, Shengyi Ji, Zhen Tian, Hongbo Jiang, Weiguo Zheng, Xuecang Zhang |
| 2023 | M3PT: A Multi-Modal Model for POI Tagging. JingSong Yang, Guanzhou Han, Deqing Yang, Jingping Liu, Yanghua Xiao, Xiang Xu, Baohua Wu, Shenghua Ni |
| 2023 | M5: Multi-Modal Multi-Interest Multi-Scenario Matching for Over-the-Top Recommendation. Pengyu Zhao, Xin Gao, Chunxu Xu, Liang Chen |
| 2023 | MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction. Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang |
| 2023 | MAPLE: Semi-Supervised Learning with Multi-Alignment and Pseudo-Learning. Juncheng Yang, Chao Li, Zuchao Li, Wei Yu, Bo Du, Shijun Li |
| 2023 | MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals. Donghong Cai, Junru Chen, Yang Yang, Teng Liu, Yafeng Li |
| 2023 | MGNN: Graph Neural Networks Inspired by Distance Geometry Problem. Guanyu Cui, Zhewei Wei |
| 2023 | MIDLG: Mutual Information based Dual Level GNN for Transaction Fraud Complaint Verification. Wen Zheng, Bingbing Xu, Emiao Lu, Yang Li, Qi Cao, Xuan Zong, Huawei Shen |
| 2023 | MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis. Tian Lan, Ziyue Li, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Wolfgang Ketter, Rui Zhao, Chen Zhang |
| 2023 | MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style Transfer. Yazheng Yang, Zhou Zhao, Qi Liu |
| 2023 | MUSER: A MUlti-Step Evidence Retrieval Enhancement Framework for Fake News Detection. Hao Liao, Jiahao Peng, Zhanyi Huang, Wei Zhang, Guanghua Li, Kai Shu, Xing Xie |
| 2023 | Machine Unlearning in Gradient Boosting Decision Trees. Huawei Lin, Jun Woo Chung, Yingjie Lao, Weijie Zhao |
| 2023 | Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding. Haoyu Wang, Yaqing Wang, Feijie Wu, Hongfei Xue, Jing Gao |
| 2023 | Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning. Zhengyang Zhou, Qihe Huang, Kuo Yang, Kun Wang, Xu Wang, Yudong Zhang, Yuxuan Liang, Yang Wang |
| 2023 | Mastering Stock Markets with Efficient Mixture of Diversified Trading Experts. Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An |
| 2023 | Maximizing Neutrality in News Ordering. Rishi Advani, Paolo Papotti, Abolfazl Asudeh |
| 2023 | MedLink: De-Identified Patient Health Record Linkage. Zhenbang Wu, Cao Xiao, Jimeng Sun |
| 2023 | Meta Graph Learning for Long-tail Recommendation. Chunyu Wei, Jian Liang, Di Liu, Zehui Dai, Mang Li, Fei Wang |
| 2023 | Meta Multi-agent Exercise Recommendation: A Game Application Perspective. Fei Liu, Xuegang Hu, Shuochen Liu, Chenyang Bu, Le Wu |
| 2023 | MetricPrompt: Prompting Model as a Relevance Metric for Few-shot Text Classification. Hongyuan Dong, Weinan Zhang, Wanxiang Che |
| 2023 | MicroscopeSketch: Accurate Sliding Estimation Using Adaptive Zooming. Yuhan Wu, Shiqi Jiang, Siyuan Dong, Zheng Zhong, Jiale Chen, Yutong Hu, Tong Yang, Steve Uhlig, Bin Cui |
| 2023 | MimoSketch: A Framework to Mine Item Frequency on Multiple Nodes with Sketches. Yuchen Xu, Wenfei Wu, Bohan Zhao, Tong Yang, Yikai Zhao |
| 2023 | Minimizing Hitting Time between Disparate Groups with Shortcut Edges. Florian Adriaens, Honglian Wang, Aristides Gionis |
| 2023 | Mining Electronic Health Records for Real-World Evidence. Chengxi Zang, Weishen Pan, Fei Wang |
| 2023 | Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. Geon Lee, Jaemin Yoo, Kijung Shin |
| 2023 | Mitigating Action Hysteresis in Traffic Signal Control with Traffic Predictive Reinforcement Learning. Xiao Han, Xiangyu Zhao, Liang Zhang, Wanyu Wang |
| 2023 | MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation. Jiaxing Zhang, Dongsheng Luo, Hua Wei |
| 2023 | Modeling Dual Period-Varying Preferences for Takeaway Recommendation. Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu |
| 2023 | Modelling Delayed Redemption with Importance Sampling and Pre-Redemption Engagement. Samik Datta, Anshuman Mourya, Anirban Majumder, Vineet Chaoji |
| 2023 | Multi Datasource LTV User Representation (MDLUR). Junwoo Yun, Wonryeol Kwak, Joohyun Kim |
| 2023 | Multi-Grained Multimodal Interaction Network for Entity Linking. Pengfei Luo, Tong Xu, Shiwei Wu, Chen Zhu, Linli Xu, Enhong Chen |
| 2023 | Multi-Label Learning to Rank through Multi-Objective Optimization. Debabrata Mahapatra, Chaosheng Dong, Yetian Chen, Michinari Momma |
| 2023 | Multi-Temporal Relationship Inference in Urban Areas. Shuangli Li, Jingbo Zhou, Ji Liu, Tong Xu, Enhong Chen, Hui Xiong |
| 2023 | Multi-channel Integrated Recommendation with Exposure Constraints. Yue Xu, Qijie Shen, Jianwen Yin, Zengde Deng, Dimin Wang, Hao Chen, Lixiang Lai, Tao Zhuang, Junfeng Ge |
| 2023 | Multi-factor Sequential Re-ranking with Perception-Aware Diversification. Yue Xu, Hao Chen, Zefan Wang, Jianwen Yin, Qijie Shen, Dimin Wang, Feiran Huang, Lixiang Lai, Tao Zhuang, Junfeng Ge, Xia Hu |
| 2023 | Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting. Ferdian Jovan, Catherine Morgan, Ryan McConville, Emma L. Tonkin, Ian Craddock, Alan L. Whone |
| 2023 | Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling. Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong |
| 2023 | NEON: Living Needs Prediction System in Meituan. Xiaochong Lan, Chen Gao, Shiqi Wen, Xiuqi Chen, Yingge Che, Han Zhang, Huazhou Wei, Hengliang Luo, Yong Li |
| 2023 | NFT-Based Data Marketplace with Digital Watermarking. Saeed Ranjbar Alvar, Mohammad Akbari, David (Ming Xuan) Yue, Yong Zhang |
| 2023 | Narrow the Input Mismatch in Deep Graph Neural Network Distillation. Qiqi Zhou, Yanyan Shen, Lei Chen |
| 2023 | Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework. Jiayun Zhang, Xiyuan Zhang, Xinyang Zhang, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang |
| 2023 | Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders. Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong |
| 2023 | Neural Insights for Digital Marketing Content Design. Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti |
| 2023 | Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler. Zhijun Chen, Hailong Sun, Wanhao Zhang, Chunyi Xu, Qianren Mao, Pengpeng Chen |
| 2023 | Node Classification Beyond Homophily: Towards a General Solution. Zhe Xu, Yuzhong Chen, Qinghai Zhou, Yuhang Wu, Menghai Pan, Hao Yang, Hanghang Tong |
| 2023 | OPORP: One Permutation + One Random Projection. Ping Li, Xiaoyun Li |
| 2023 | Off-Policy Evaluation of Ranking Policies under Diverse User Behavior. Haruka Kiyohara, Masatoshi Uehara, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto, Yuta Saito |
| 2023 | Off-Policy Learning-to-Bid with AuctionGym. Olivier Jeunen, Sean Murphy, Ben Allison |
| 2023 | On Hierarchical Disentanglement of Interactive Behaviors for Multimodal Spatiotemporal Data with Incompleteness. Jiayi Chen, Aidong Zhang |
| 2023 | On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms. Fanchen Bu, Kijung Shin |
| 2023 | On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering. Jiayan Guo, Lun Du, Xu Chen, Xiaojun Ma, Qiang Fu, Shi Han, Dongmei Zhang, Yan Zhang |
| 2023 | On Structural Expressive Power of Graph Transformers. Wenhao Zhu, Tianyu Wen, Guojie Song, Liang Wang, Bo Zheng |
| 2023 | On-device Integrated Re-ranking with Heterogeneous Behavior Modeling. Yunjia Xi, Weiwen Liu, Yang Wang, Ruiming Tang, Weinan Zhang, Yue Zhu, Rui Zhang, Yong Yu |
| 2023 | One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud Platforms. Shaoyuan Huang, Zheng Wang, Heng Zhang, Xiaofei Wang, Cheng Zhang, Wenyu Wang |
| 2023 | One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong |
| 2023 | Online Fairness Auditing through Iterative Refinement. Pranav Maneriker, Codi Burley, Srinivasan Parthasarathy |
| 2023 | Online Few-Shot Time Series Classification for Aftershock Detection. Sheng Zhong, Vinícius M. A. de Souza, Glenn Eli Baker, Abdullah Mueen |
| 2023 | Online Level-wise Hierarchical Clustering. Nicholas Monath, Manzil Zaheer, Andrew McCallum |
| 2023 | Online Quality Prediction in Windshield Manufacturing using Data-Efficient Machine Learning. Hasan Tercan, Tobias Meisen |
| 2023 | Open-Set Semi-Supervised Text Classification with Latent Outlier Softening. Junfan Chen, Richong Zhang, Junchi Chen, Chunming Hu, Yongyi Mao |
| 2023 | Optimal Dynamic Subset Sampling: Theory and Applications. Lu Yi, Hanzhi Wang, Zhewei Wei |
| 2023 | Optimizing Airbnb Search Journey with Multi-task Learning. Chun How Tan, Austin Chan, Malay Haldar, Jie Tang, Xin Liu, Mustafa Abdool, Huiji Gao, Liwei He, Sanjeev Katariya |
| 2023 | Optimizing Traffic Control with Model-Based Learning: A Pessimistic Approach to Data-Efficient Policy Inference. Mayuresh Kunjir, Sanjay Chawla, Siddarth Chandrasekar, Devika Jay, Balaraman Ravindran |
| 2023 | PASS: Personalized Advertiser-aware Sponsored Search. Zhoujin Tian, Chaozhuo Li, Zhiqiang Zuo, Zengxuan Wen, Lichao Sun, Xinyue Hu, Wen Zhang, Haizhen Huang, Senzhang Wang, Weiwei Deng, Xing Xie, Qi Zhang |
| 2023 | PAT: Geometry-Aware Hard-Label Black-Box Adversarial Attacks on Text. Muchao Ye, Jinghui Chen, Chenglin Miao, Han Liu, Ting Wang, Fenglong Ma |
| 2023 | PDAS: A Practical Distributed ADMM System for Large-Scale Linear Programming Problems at Alipay. Jun Zhou, Yang Bao, Daohong Jian, Hua Wu |
| 2023 | PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information. Jianxin Chang, Chenbin Zhang, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai |
| 2023 | PERT-GNN: Latency Prediction for Microservice-based Cloud-Native Applications via Graph Neural Networks. Da Sun Handason Tam, Yang Liu, Huanle Xu, Siyue Xie, Wing Cheong Lau |
| 2023 | PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation. Xuewu Jiao, Weibin Li, Xinxuan Wu, Wei Hu, Miao Li, Jiang Bian, Siming Dai, Xinsheng Luo, Mingqing Hu, Zhengjie Huang, Danlei Feng, Junchao Yang, Shikun Feng, Haoyi Xiong, Dianhai Yu, Shuanglong Li, Jingzhou He, Yanjun Ma, Lin Liu |
| 2023 | PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce. Xiaowen Shi, Fan Yang, Ze Wang, Xiaoxu Wu, Muzhi Guan, Guogang Liao, Yongkang Wang, Xingxing Wang, Dong Wang |
| 2023 | PROSE: Graph Structure Learning via Progressive Strategy. Huizhao Wang, Yao Fu, Tao Yu, Linghui Hu, Weihao Jiang, Shiliang Pu |
| 2023 | PSLOG: Pretraining with Search Logs for Document Ranking. Zhan Su, Zhicheng Dou, Yujia Zhou, Ziyuan Zhao, Ji-Rong Wen |
| 2023 | Parameter-free Spikelet: Discovering Different Length and Warped Time Series Motifs using an Adaptive Time Series Representation. Makoto Imamura, Takaaki Nakamura |
| 2023 | Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples. Shuo He, Lei Feng, Guowu Yang |
| 2023 | Path-Specific Counterfactual Fairness for Recommender Systems. Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li |
| 2023 | Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction. Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, Lei Bai, Yang Wang |
| 2023 | Personalized Federated Learning with Parameter Propagation. Jun Wu, Wenxuan Bao, Elizabeth A. Ainsworth, Jingrui He |
| 2023 | Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations. Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Tian Tian, Jun Zhu |
| 2023 | PlanRanker: Towards Personalized Ranking of Train Transfer Plans. Jia Xu, Wanjie Tao, Zulong Chen, Jin Huang, Huihui Liu, Hong Wen, Shenghua Ni, Qun Dai, Yu Gu |
| 2023 | Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting. Christine Herlihy, Aviva Prins, Aravind Srinivasan, John P. Dickerson |
| 2023 | Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference. Aman Gupta, S. Sathiya Keerthi, Ayan Acharya, Miao Cheng, Borja Ocejo Elizondo, Rohan Ramanath, Rahul Mazumder, Kinjal Basu, J. Kenneth Tay, Rupesh Gupta |
| 2023 | Practical Synthetic Human Trajectories Generation Based on Variational Point Processes. Qingyue Long, Huandong Wang, Tong Li, Lisi Huang, Kun Wang, Qiong Wu, Guangyu Li, Yanping Liang, Li Yu, Yong Li |
| 2023 | Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design. Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu |
| 2023 | Precision Health in the Age of Large Language Models. Hoifung Poon, Tristan Naumann, Sheng Zhang, Javier González Hernández |
| 2023 | Precursor-of-Anomaly Detection for Irregular Time Series. Sheo Yon Jhin, Jaehoon Lee, Noseong Park |
| 2023 | Predicting Information Pathways Across Online Communities. Yiqiao Jin, Yeon-Chang Lee, Kartik Sharma, Meng Ye, Karan Sikka, Ajay Divakaran, Srijan Kumar |
| 2023 | Preemptive Detection of Fake Accounts on Social Networks via Multi-Class Preferential Attachment Classifiers. Adam Breuer, Nazanin Khosravani Tehrani, Michael Tingley, Bradford Cottel |
| 2023 | PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement. Wanqi Xue, Qingpeng Cai, Zhenghai Xue, Shuo Sun, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An |
| 2023 | Prescriptive PCA: Dimensionality Reduction for Two-stage Stochastic Optimization. Long He, Ho-Yin Mak |
| 2023 | Pretrained Language Representations for Text Understanding: A Weakly-Supervised Perspective. Yu Meng, Jiaxin Huang, Yu Zhang, Yunyi Zhang, Jiawei Han |
| 2023 | Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation. Zeyu Cao, Zhipeng Liang, Bingzhe Wu, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao |
| 2023 | Privacy in Advertising: Analytics and Modeling. Badih Ghazi, Ravi Kumar, Pasin Manurangsi |
| 2023 | PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation. Ruixuan Liu, Yang Cao, Yanlin Wang, Lingjuan Lyu, Yun Chen, Hong Chen |
| 2023 | Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023 Ambuj K. Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar, Fatma Ozcan, Jieping Ye |
| 2023 | PyHealth: A Deep Learning Toolkit for Healthcare Applications. Chaoqi Yang, Zhenbang Wu, Patrick Jiang, Zhen Lin, Junyi Gao, Benjamin P. Danek, Jimeng Sun |
| 2023 | Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-scale Disentangled Representations. Haoyu Geng, Chao Chen, Yixuan He, Gang Zeng, Zhaobing Han, Hua Chai, Junchi Yan |
| 2023 | QTIAH-GNN: Quantity and Topology Imbalance-aware Heterogeneous Graph Neural Network for Bankruptcy Prediction. Yucheng Liu, Zipeng Gao, Xiangyang Liu, Pengfei Luo, Yang Yang, Hui Xiong |
| 2023 | QTNet: Theory-based Queue Length Prediction for Urban Traffic. Ryu Shirakami, Toshiya Kitahara, Koh Takeuchi, Hisashi Kashima |
| 2023 | QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search. Jian Xie, Yidan Liang, Jingping Liu, Yanghua Xiao, Baohua Wu, Shenghua Ni |
| 2023 | Quantifying Node Importance over Network Structural Stability. Fan Zhang, Qingyuan Linghu, Jiadong Xie, Kai Wang, Xuemin Lin, Wenjie Zhang |
| 2023 | Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization. Yunze Tong, Junkun Yuan, Min Zhang, Didi Zhu, Keli Zhang, Fei Wu, Kun Kuang |
| 2023 | Querywise Fair Learning to Rank through Multi-Objective Optimization. Debabrata Mahapatra, Chaosheng Dong, Michinari Momma |
| 2023 | R-Mixup: Riemannian Mixup for Biological Networks. Xuan Kan, Zimu Li, Hejie Cui, Yue Yu, Ran Xu, Shaojun Yu, Zilong Zhang, Ying Guo, Carl Yang |
| 2023 | RLTP: Reinforcement Learning to Pace for Delayed Impression Modeling in Preloaded Ads. Penghui Wei, Yongqiang Chen, Shaoguo Liu, Liang Wang, Bo Zheng |
| 2023 | Rank-heterogeneous Preference Models for School Choice. Amel Awadelkarim, Arjun Seshadri, Itai Ashlagi, Irene Lo, Johan Ugander |
| 2023 | RankFormer: Listwise Learning-to-Rank Using Listwide Labels. Maarten Buyl, Paul Missault, Pierre-Antoine Sondag |
| 2023 | Rapid Image Labeling via Neuro-Symbolic Learning. Yifeng Wang, Zhi Tu, Yiwen Xiang, Shiyuan Zhou, Xiyuan Chen, Bingxuan Li, Tianyi Zhang |
| 2023 | ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. Jieming Zhu, Guohao Cai, Junjie Huang, Zhenhua Dong, Ruiming Tang, Weinan Zhang |
| 2023 | Real Time Index and Search Across Large Quantities of GNN Experts for Low Latency Online Learning. Johan Kok Zhi Kang, Sien Yi Tan, Bingsheng He, Zhen Zhang |
| 2023 | Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation. Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen |
| 2023 | Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. Teng Xiao, Zhengyu Chen, Suhang Wang |
| 2023 | Reconstructing Graph Diffusion History from a Single Snapshot. Ruizhong Qiu, Dingsu Wang, Lei Ying, H. Vincent Poor, Yifang Zhang, Hanghang Tong |
| 2023 | RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent Recruitment. Chuyu Fang, Chuan Qin, Qi Zhang, Kaichun Yao, Jingshuai Zhang, Hengshu Zhu, Fuzhen Zhuang, Hui Xiong |
| 2023 | Reducing Exposure to Harmful Content via Graph Rewiring. Corinna Coupette, Stefan Neumann, Aristides Gionis |
| 2023 | RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang |
| 2023 | Removing Camouflage and Revealing Collusion: Leveraging Gang-crime Pattern in Fraudster Detection. Lewen Wang, Haozhe Zhao, Cunguang Feng, Weiqing Liu, Congrui Huang, Marco Santoni, Manuel Cristofaro, Paola Jafrancesco, Jiang Bian |
| 2023 | Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers. Chanyoung Chung, Jaejun Lee, Joyce Jiyoung Whang |
| 2023 | Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment. Atharva Kulkarni, Sarah Masud, Vikram Goyal, Tanmoy Chakraborty |
| 2023 | Revisiting Neural Retrieval on Accelerators. Jiaqi Zhai, Zhaojie Gong, Yueming Wang, Xiao Sun, Zheng Yan, Fu Li, Xing Liu |
| 2023 | Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng |
| 2023 | Rewiring Police Officer Training Networks to Reduce Forecasted Use of Force. Ritika Pandey, Jeremy G. Carter, James H. Hill, George O. Mohler |
| 2023 | Road Planning for Slums via Deep Reinforcement Learning. Yu Zheng, Hongyuan Su, Jingtao Ding, Depeng Jin, Yong Li |
| 2023 | Robust Multimodal Failure Detection for Microservice Systems. Chenyu Zhao, Minghua Ma, Zhenyu Zhong, Shenglin Zhang, Zhiyuan Tan, Xiao Xiong, Lulu Yu, Jiayi Feng, Yongqian Sun, Yuzhi Zhang, Dan Pei, Qingwei Lin, Dongmei Zhang |
| 2023 | Robust NLP for Finance (RobustFin). Sameena Shah, Xiaodan Zhu, Gerard de Melo, Armineh Nourbakhsh, Xiaomo Liu, Zhiqiang Ma, Charese Smiley, Zhiyu Chen |
| 2023 | Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction. Zhangchi Zhu, Lu Wang, Pu Zhao, Chao Du, Wei Zhang, Hang Dong, Bo Qiao, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang |
| 2023 | Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training. Fan Liu, Weijia Zhang, Hao Liu |
| 2023 | Robustness Certification for Structured Prediction with General Inputs via Safe Region Modeling in the Semimetric Output Space. Huaqing Shao, Lanjun Wang, Junchi Yan |
| 2023 | Root Cause Analysis for Microservice Systems via Hierarchical Reinforcement Learning from Human Feedback. Lu Wang, Chaoyun Zhang, Ruomeng Ding, Yong Xu, Qihang Chen, Wentao Zou, Qingjun Chen, Meng Zhang, Xuedong Gao, Hao Fan, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang |
| 2023 | Rover: An Online Spark SQL Tuning Service via Generalized Transfer Learning. Yu Shen, Xinyuyang Ren, Yupeng Lu, Huaijun Jiang, Huanyong Xu, Di Peng, Yang Li, Wentao Zhang, Bin Cui |
| 2023 | Rumor Detection with Diverse Counterfactual Evidence. Kaiwei Zhang, Junchi Yu, Haichao Shi, Jian Liang, Xiaoyu Zhang |
| 2023 | S Yuchen Li, Haoyi Xiong, Linghe Kong, Qingzhong Wang, Shuaiqiang Wang, Guihai Chen, Dawei Yin |
| 2023 | SAInf: Stay Area Inference of Vehicles using Surveillance Camera Records. Zhipeng Ma, Chuishi Meng, Huimin Ren, Sijie Ruan, Jie Bao, Xiaoting Wang, Tianrui Li, Yu Zheng |
| 2023 | SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation. Zhaoxin Huan, Ang Li, Xiaolu Zhang, Xu Min, Jieyu Yang, Yong He, Jun Zhou |
| 2023 | SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky |
| 2023 | ST-iFGSM: Enhancing Robustness of Human Mobility Signature Identification Model via Spatial-Temporal Iterative FGSM. Mingzhi Hu, Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo |
| 2023 | SURE: Robust, Explainable, and Fair Classification without Sensitive Attributes. Deepayan Chakrabarti |
| 2023 | Scenario-Adaptive Feature Interaction for Click-Through Rate Prediction. Erxue Min, Da Luo, Kangyi Lin, Chunzhen Huang, Yang Liu |
| 2023 | Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning. Weiguang Han, Boyi Zhang, Qianqian Xie, Min Peng, Yanzhao Lai, Jimin Huang |
| 2023 | Self-Adaptive Perturbation Radii for Adversarial Training. Huimin Wu, Wanli Shi, Chenkang Zhang, Bin Gu |
| 2023 | Self-supervised Classification of Clinical Multivariate Time Series using Time Series Dynamics. Yakir Yehuda, Daniel Freedman, Kira Radinsky |
| 2023 | Semantic Dissimilarity Guided Locality Preserving Projections for Partial Label Dimensionality Reduction. Yuheng Jia, Jiahao Jiang, Yongheng Wang |
| 2023 | Semantic-Enhanced Differentiable Search Index Inspired by Learning Strategies. Yubao Tang, Ruqing Zhang, Jiafeng Guo, Jiangui Chen, Zuowei Zhu, Shuaiqiang Wang, Dawei Yin, Xueqi Cheng |
| 2023 | Semi-Supervised Graph Imbalanced Regression. Gang Liu, Tong Zhao, Eric Inae, Tengfei Luo, Meng Jiang |
| 2023 | SentiGOLD: A Large Bangla Gold Standard Multi-Domain Sentiment Analysis Dataset and Its Evaluation. Md. Ekramul Islam, Labib Chowdhury, Faisal Ahamed Khan, Shazzad Hossain, Md. Sourave Hossain, Mohammad Mamun Or Rashid, Nabeel Mohammed, Mohammad Ruhul Amin |
| 2023 | Sequence As Genes: An User Behavior Modeling Framework for Fraud Transaction Detection in E-commerce. Ziming Wang, Qianru Wu, Baolin Zheng, Junjie Wang, Kaiyu Huang, Yanjie Shi |
| 2023 | Sequential Learning Algorithms for Contextual Model-Free Influence Maximization. Alexandra Iacob, Bogdan Cautis, Silviu Maniu |
| 2023 | Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. Xidong Wu, Zhengmian Hu, Jian Pei, Heng Huang |
| 2023 | ShapleyFL: Robust Federated Learning Based on Shapley Value. Qiheng Sun, Xiang Li, Jiayao Zhang, Li Xiong, Weiran Liu, Jinfei Liu, Zhan Qin, Kui Ren |
| 2023 | Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term. Yun Yue, Jiadi Jiang, Zhiling Ye, Ning Gao, Yongchao Liu, Ke Zhang |
| 2023 | Shift-Robust Molecular Relational Learning with Causal Substructure. Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, Sein Kim, Chanyoung Park |
| 2023 | Shilling Black-box Review-based Recommender Systems through Fake Review Generation. Hung-Yun Chiang, Yi-Syuan Chen, Yun-Zhu Song, Hong-Han Shuai, Jason S. Chang |
| 2023 | ShuttleSet: A Human-Annotated Stroke-Level Singles Dataset for Badminton Tactical Analysis. Wei-Yao Wang, Yung-Chang Huang, Tsi-Ui Ik, Wen-Chih Peng |
| 2023 | Similarity Preserving Adversarial Graph Contrastive Learning. Yeonjun In, Kanghoon Yoon, Chanyoung Park |
| 2023 | Sketch-Based Anomaly Detection in Streaming Graphs. Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi |
| 2023 | SketchPolymer: Estimate Per-item Tail Quantile Using One Sketch. Jiarui Guo, Yisen Hong, Yuhan Wu, Yunfei Liu, Tong Yang, Bin Cui |
| 2023 | Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen |
| 2023 | Socially Responsible Machine Learning: A Causal Perspective. Raha Moraffah, Amir-Hossein Karimi, Adrienne Raglin, Huan Liu |
| 2023 | Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen |
| 2023 | Sparse Binary Transformers for Multivariate Time Series Modeling. Matt Gorbett, Hossein Shirazi, Indrakshi Ray |
| 2023 | Spatial Clustering Regression of Count Value Data via Bayesian Mixture of Finite Mixtures. Peng Zhao, Hou-Cheng Yang, Dipak K. Dey, Guanyu Hu |
| 2023 | Spatial Heterophily Aware Graph Neural Networks. Congxi Xiao, Jingbo Zhou, Jizhou Huang, Tong Xu, Hui Xiong |
| 2023 | Spatio-temporal Diffusion Point Processes. Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin, Yong Li |
| 2023 | Specify Robust Causal Representation from Mixed Observations. Mengyue Yang, Xinyu Cai, Furui Liu, Weinan Zhang, Jun Wang |
| 2023 | Stabilising Job Survival Analysis for Disability Employment Services in Unseen Environments. Ha Xuan Tran, Thuc Duy Le, Jiuyong Li, Lin Liu, Xiaomei Li, Jixue Liu, Tony Waters |
| 2023 | Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem. Jiayi Liu, Jennifer Neville |
| 2023 | TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam |
| 2023 | TWIN: Personalized Clinical Trial Digital Twin Generation. Trisha Das, Zifeng Wang, Jimeng Sun |
| 2023 | TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou. Jianxin Chang, Chenbin Zhang, Zhiyi Fu, Xiaoxue Zang, Lin Guan, Jing Lu, Yiqun Hui, Dewei Leng, Yanan Niu, Yang Song, Kun Gai |
| 2023 | Taming the Domain Shift in Multi-source Learning for Energy Disaggregation. Xiaomin Chang, Wei Li, Yunchuan Shi, Albert Y. Zomaya |
| 2023 | Task Relation-aware Continual User Representation Learning. Sein Kim, Namkyeong Lee, Donghyun Kim, Min-Chul Yang, Chanyoung Park |
| 2023 | Task-Equivariant Graph Few-shot Learning. Sungwon Kim, Junseok Lee, Namkyeong Lee, Wonjoong Kim, Seungyoon Choi, Chanyoung Park |
| 2023 | Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models. Kartik Sharma, Rakshit S. Trivedi, Rohit Sridhar, Srijan Kumar |
| 2023 | Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data. Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney |
| 2023 | Text Is All You Need: Learning Language Representations for Sequential Recommendation. Jiacheng Li, Ming Wang, Jin Li, Jinmiao Fu, Xin Shen, Jingbo Shang, Julian J. McAuley |
| 2023 | The 12th International Workshop on Urban Computing. Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson |
| 2023 | The 3rd Workshop on Artificial Intelligence-enabled Cybersecurity Analytics. Sagar Samtani, Shanchieh Yang, Hsinchun Chen |
| 2023 | The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik |
| 2023 | The 4th International Workshop on Talent and Management Computing (TMC'2023). Hengshu Zhu, Hui Xiong, Yong Ge, Ee-Peng Lim |
| 2023 | The 6th Workshop on e-eommerce and NLP (ECNLP 6). Shervin Malmasi, Besnik Fetahu, Eugene Agichtein, Oleg Rokhlenko, Ido Guy, Nicola Ueffing, Surya Kallumadi |
| 2023 | The 9th SIGKDD International Workshop on Mining and Learning from Time Series. Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Yuriy Nevmyvaka |
| 2023 | The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles. Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian |
| 2023 | The KDD'23 Workshop on Causal Discovery, Prediction and Decision (CDPD 2023). Thuc Duy Le |
| 2023 | The Missing Indicator Method: From Low to High Dimensions. Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell |
| 2023 | The Second Workshop on Applied Machine Learning Management. Dmitri Goldenberg, Chana Ross, Shir Meir Lador, Lin Lee Cheong, Panpan Xu, Elena Sokolova, Amit Mandelbaum, Irina Vasilinetc, Ankit Jain, Amit Weil Modlinger, Saloni Potdar |
| 2023 | The Second Workshop on Knowledge-Augmented Methods for Natural Language Processing. Wenhao Yu, Lingbo Tong, Weijia Shi, Nanyun Peng, Meng Jiang |
| 2023 | Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity. Yangyang Wang, Xiao Zhang, Mingyi Li, Tian Lan, Huashan Chen, Hui Xiong, Xiuzhen Cheng, Dongxiao Yu |
| 2023 | Time-to-Event Modeling with Hypernetwork based Hawkes Process. Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar |
| 2023 | To Aggregate or Not? Learning with Separate Noisy Labels. Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu |
| 2023 | Towards Disentangling Relevance and Bias in Unbiased Learning to Rank. Yunan Zhang, Le Yan, Zhen Qin, Honglei Zhuang, Jiaming Shen, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2023 | Towards Equitable Assignment: Data-Driven Delivery Zone Partition at Last-mile Logistics. Baoshen Guo, Shuai Wang, Haotian Wang, Yunhuai Liu, Fanshuo Kong, Desheng Zhang, Tian He |
| 2023 | Towards Fair Disentangled Online Learning for Changing Environments. Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen |
| 2023 | Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learning. Aditya Srinivas Timmaraju, Mehdi Mashayekhi, Mingliang Chen, Qi Zeng, Quintin Fettes, Wesley Cheung, Yihan Xiao, Manojkumar Rangasamy Kannadasan, Pushkar Tripathi, Sean Gahagan, Miranda Bogen, Rob Roudani |
| 2023 | Towards Graph-level Anomaly Detection via Deep Evolutionary Mapping. Xiaoxiao Ma, Jia Wu, Jian Yang, Quan Z. Sheng |
| 2023 | Towards Next-Generation Intelligent Assistants Leveraging LLM Techniques. Xin Luna Dong, Seungwhan Moon, Yifan Ethan Xu, Kshitiz Malik, Zhou Yu |
| 2023 | Towards Reliable Rare Category Analysis on Graphs via Individual Calibration. Longfeng Wu, Bowen Lei, Dongkuan Xu, Dawei Zhou |
| 2023 | Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning. Daeun Lee, Sejung Son, Hyolim Jeon, Seungbae Kim, Jinyoung Han |
| 2023 | Towards Understanding and Enhancing Robustness of Deep Learning Models against Malicious Unlearning Attacks. Wei Qian, Chenxu Zhao, Wei Le, Meiyi Ma, Mengdi Huai |
| 2023 | Towards Variance Reduction for Reinforcement Learning of Industrial Decision-making Tasks: A Bi-Critic based Demand-Constraint Decoupling Approach. Jianyong Yuan, Jiayi Zhang, Zinuo Cai, Junchi Yan |
| 2023 | Towards a Generic Framework for Mechanism-guided Deep Learning for Manufacturing Applications. Hanbo Zhang, Jiangxin Li, Shen Liang, Peng Wang, Themis Palpanas, Chen Wang, Wei Wang, Haoxuan Zhou, Jianwei Song, Wen Lu |
| 2023 | Training Large-scale Foundation Models on Emerging AI Chips. Aashiq Muhamed, Christian Bock, Rahul Solanki, Youngsuk Park, Yida Wang, Jun Huan |
| 2023 | TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest. Xue Xia, Pong Eksombatchai, Nikil Pancha, Dhruvil Deven Badani, Po-Wei Wang, Neng Gu, Saurabh Vishwas Joshi, Nazanin Farahpour, Zhiyuan Zhang, Andrew Zhai |
| 2023 | Transferable Graph Structure Learning for Graph-based Traffic Forecasting Across Cities. Yilun Jin, Kai Chen, Qiang Yang |
| 2023 | TransformerLight: A Novel Sequence Modeling Based Traffic Signaling Mechanism via Gated Transformer. Qiang Wu, Mingyuan Li, Jun Shen, Linyuan Lü, Bo Du, Ke Zhang |
| 2023 | Treatment Effect Estimation with Adjustment Feature Selection. Haotian Wang, Kun Kuang, Haoang Chi, Longqi Yang, Mingyang Geng, Wanrong Huang, Wenjing Yang |
| 2023 | Tree based Progressive Regression Model for Watch-Time Prediction in Short-video Recommendation. Xiao Lin, Xiaokai Chen, Linfeng Song, Jingwei Liu, Biao Li, Peng Jiang |
| 2023 | TrustGeo: Uncertainty-Aware Dynamic Graph Learning for Trustworthy IP Geolocation. Wenxin Tai, Bin Chen, Fan Zhou, Ting Zhong, Goce Trajcevski, Yong Wang, Kai Chen |
| 2023 | Trustworthy Machine Learning: Robustness, Generalization, and Interpretability. Jindong Wang, Haoliang Li, Haohan Wang, Sinno Jialin Pan, Xing Xie |
| 2023 | Trustworthy Recommender Systems: Foundations and Frontiers. Wenqi Fan, Xiangyu Zhao, Lin Wang, Xiao Chen, Jingtong Gao, Qidong Liu, Shijie Wang |
| 2023 | Trustworthy Transfer Learning: Transferability and Trustworthiness. Jun Wu, Jingrui He |
| 2023 | TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twitter. Xinyang Zhang, Yury Malkov, Omar Florez, Serim Park, Brian McWilliams, Jiawei Han, Ahmed El-Kishky |
| 2023 | UA-FedRec: Untargeted Attack on Federated News Recommendation. Jingwei Yi, Fangzhao Wu, Bin Zhu, Jing Yao, Zhulin Tao, Guangzhong Sun, Xing Xie |
| 2023 | UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation. Jiacheng Li, Zhankui He, Jingbo Shang, Julian J. McAuley |
| 2023 | Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction. Yifan Wang, Peijie Sun, Min Zhang, Qinglin Jia, Jingjie Li, Shaoping Ma |
| 2023 | Unbiased Locally Private Estimator for Polynomials of Laplacian Variables. Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya |
| 2023 | Uncertainty Quantification in Deep Learning. Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang |
| 2023 | Uncertainty-Aware Probabilistic Travel Time Prediction for On-Demand Ride-Hailing at DiDi. Hao Liu, Wenzhao Jiang, Shui Liu, Xi Chen |
| 2023 | Understanding the Semantics of GPS-based Trajectories for Road Closure Detection. Jiasheng Zhang, Kaiqiang An, Guoping Liu, Xiang Wen, Runbo Hu, Jie Shao |
| 2023 | UnifieR: A Unified Retriever for Large-Scale Retrieval. Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Kai Zhang, Daxin Jiang |
| 2023 | Urban Region Representation Learning with OpenStreetMap Building Footprints. Yi Li, Weiming Huang, Gao Cong, Hao Wang, Zheng Wang |
| 2023 | User-Regulation Deconfounded Conversational Recommender System with Bandit Feedback. Yu Xia, Junda Wu, Tong Yu, Sungchul Kim, Ryan A. Rossi, Shuai Li |
| 2023 | Using Motif Transitions for Temporal Graph Generation. Penghang Liu, Ahmet Erdem Sariyüce |
| 2023 | VQNE: Variational Quantum Network Embedding with Application to Network Alignment. Xinyu Ye, Ge Yan, Junchi Yan |
| 2023 | VRDU: A Benchmark for Visually-rich Document Understanding. Zilong Wang, Yichao Zhou, Wei Wei, Chen-Yu Lee, Sandeep Tata |
| 2023 | Variance Reduction Using In-Experiment Data: Efficient and Targeted Online Measurement for Sparse and Delayed Outcomes. Alex Deng, Michelle Du, Anna Matlin, Qing Zhang |
| 2023 | Virtual Node Tuning for Few-shot Node Classification. Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu |
| 2023 | WHEN: A Wavelet-DTW Hybrid Attention Network for Heterogeneous Time Series Analysis. Jingyuan Wang, Chen Yang, Xiaohan Jiang, Junjie Wu |
| 2023 | Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series. Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li |
| 2023 | Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers. Yu Zhang, Bowen Jin, Xiusi Chen, Yanzhen Shen, Yunyi Zhang, Yu Meng, Jiawei Han |
| 2023 | Web-Scale Academic Name Disambiguation: The WhoIsWho Benchmark, Leaderboard, and Toolkit. Bo Chen, Jing Zhang, Fanjin Zhang, Tianyi Han, Yuqing Cheng, Xiaoyan Li, Yuxiao Dong, Jie Tang |
| 2023 | Web-based Long-term Spine Treatment Outcome Forecasting. Hangting Ye, Zhining Liu, Wei Cao, Amir M. Amiri, Jiang Bian, Yi Chang, Jon D. Lurie, Jim Weinstein, Tie-Yan Liu |
| 2023 | WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences. Xiao Liu, Hanyu Lai, Hao Yu, Yifan Xu, Aohan Zeng, Zhengxiao Du, Peng Zhang, Yuxiao Dong, Jie Tang |
| 2023 | What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang |
| 2023 | When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash |
| 2023 | When to Pre-Train Graph Neural Networks? From Data Generation Perspective! Yuxuan Cao, Jiarong Xu, Carl Yang, Jiaan Wang, Yunchao Zhang, Chunping Wang, Lei Chen, Yang Yang |
| 2023 | Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. Haoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui |
| 2023 | WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window. Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, Jie Tang |
| 2023 | Workplace Recommendation with Temporal Network Objectives. Kiran Tomlinson, Jennifer Neville, Longqi Yang, Mengting Wan, Cao Lu |
| 2023 | Workshop on Applied Data Science for Healthcare: Applications and New Frontiers of Generative Models for Healthcare. Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner |
| 2023 | XAI for Predictive Maintenance. João Gama, Slawomir Nowaczyk, Sepideh Pashami, Rita P. Ribeiro, Grzegorz J. Nalepa, Bruno Veloso |
| 2023 | Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library. Mathieu Guillame-Bert, Sebastian Bruch, Richard Stotz, Jan Pfeifer |
| 2023 | epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. Bijaya Adhikari, Alexander Rodríguez, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash |
| 2023 | iETA: A Robust and Scalable Incremental Learning Framework for Time-of-Arrival Estimation. Jindong Han, Hao Liu, Shui Liu, Xi Chen, Naiqiang Tan, Hua Chai, Hui Xiong |
| 2023 | un-xPass: Measuring Soccer Player's Creativity. Pieter Robberechts, Maaike Van Roy, Jesse Davis |
| 2023 | κHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning. Menglin Yang, Min Zhou, Lujia Pan, Irwin King |