| 2024 | A Bayesian Hierarchical Model for Orthogonal Tucker Decomposition with Oblivious Tensor Compression. Matthew Pietrosanu, Bei Jiang, Linglong Kong |
| 2024 | A Learned Approach to Index Algorithm Selection. Chaohong Ma, Xiaohui Yu, Yifan Li, Aishan Maoliniyazi, Xiaofeng Meng |
| 2024 | A Momentum Contrastive Learning Framework for Query-POI Matching. Yuting Qiang, Jianbing Zheng, Lixia Wu, Haomin Wen, Junhong Lou, Minhui Deng |
| 2024 | A Novel Shadow Variable Catcher for Addressing Selection Bias in Recommendation Systems. Qingfeng Chen, Boquan Wei, Debo Cheng, Jiuyong Li, Lin Liu, Shichao Zhang |
| 2024 | A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems. Jun Yuan, Guohao Cai, Zhenghua Dong |
| 2024 | ADOD: Adaptive Density Outlier Detection. Li Qian, Jing Qian, Xin Sun, Wengang Guo, Christian Böhm |
| 2024 | APOLLO: Differential Private Online Multi-Sensor Data Prediction with Certified Performance. Honghui Xu, Wei Li, Shaoen Wu, Liang Zhao, Zhipeng Cai |
| 2024 | Accurate and Fast Estimation of Temporal Motifs Using Path Sampling. Yunjie Pan, Omkar Bhalerao, C. Seshadhri, Nishil Talati |
| 2024 | Adaptive Graph Neural Networks for Cold-Start Multimedia Recommendation. Zhen Li, Jibin Wang, Zhuo Chen, Kun Wu, Yuanzhen Wei, Hai Huang |
| 2024 | Adaptive Loss-aware Modulation for Multimedia Retrieval. Jian Zhu, Yu Cui, Lei Liu, Zeyi Sun, Yuyang Dai, Xi Wang, Cheng Luo, Li-Rong Dai |
| 2024 | Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations. Runlong Yu, Chonghao Qiu, Robert Ladwig, Paul C. Hanson, Yiqun Xie, Yanhua Li, Xiaowei Jia |
| 2024 | Addressing Delayed Feedback in Conversion Rate Prediction: A Domain Adaptation Approach. Leisheng Yu, Yanxiao Cai, Lucas Chen, Minxing Zhang, Wei-Yen Day, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu |
| 2024 | Align Along Time and Space: A Graph Latent Diffusion Model for Traffic Dynamics Prediction. Yuhang Liu, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Sahar Ghanipoor Machiani, Yanhua Li, Jun Luo |
| 2024 | An Efficient Graph Autoencoder with Lightweight Desmoothing Decoder and Long-Range Modeling. Jinyong Wen, Tao Zhang, Chunxia Zhang, Shiming Xiang, Chunhong Pan |
| 2024 | An Explainable Recommender System by Integrating Graph Neural Networks and User Reviews. Sahar Batmani, Parham Moradi, Narges Heidari, Mahdi Jalili |
| 2024 | AnomalyLLM: Few-Shot Anomaly Edge Detection for Dynamic Graphs Using Large Language Models. Shuo Liu, Di Yao, Lanting Fang, Zhetao Li, Wenbin Li, Kaiyu Feng, Xiaowen Ji, Jingping Bi |
| 2024 | Bi-Level User Modeling for Deep Recommenders. Yejing Wang, Dong Xu, Xiangyu Zhao, Zhiren Mao, Peng Xiang, Ling Yan, Yao Hu, Zijian Zhang, Xuetao Wei, Qidong Liu |
| 2024 | CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence. Zao Zhang, Huaming Chen, Pei Ning, Nan Yang, Dong Yuan |
| 2024 | CL4CO: A Curriculum Training Framework for Graph-Based Neural Combinatorial Optimization. Yang Liu, Chuan Zhou, Peng Zhang, Zhao Li, Shuai Zhang, Xixun Lin, Xindong Wu |
| 2024 | Cascading Multimodal Feature Enhanced Contrast Learning for Music Recommendation. Qimeng Yang, Shijia Wang, Da Guo, Dongjin Yu, Qiang Xiao, Dongjing Wang, Chuanjiang Luo |
| 2024 | Channel-Attentive Graph Neural Networks. Tugrul Hasan Karabulut, Inci M. Baytas |
| 2024 | ChronoCTI: Mining Knowledge Graph of Temporal Relations Among Cyberattack Actions. Rayhanur Rahman, Brandon Wroblewski, Quinn Matthews, Brantley Morgan, Timothy Menzies, Laurie A. Williams |
| 2024 | Combining Self-Supervision and Privileged Information for Representation Learning from Tabular Data. Haoyu Yang, Michael S. Steinbach, Genevieve B. Melton, Vipin Kumar, György J. Simon |
| 2024 | Constructing $\epsilon$-Constrained Sparsified $\beta^{s}$-Complexes using Space Partitioning Trees. Rohit P. Singh, Philip A. Wilsey |
| 2024 | Continuous Exact Explanations of Neural Networks. Alice Dethise, Marco Canini |
| 2024 | Contrastive Learning for Adapting Language Model to Sequential Recommendation. Fei-Yao Liang, Wu-Dong Xi, Xing-Xing Xing, Wei Wan, Chang-Dong Wang, Min Chen, Mohsen Guizani |
| 2024 | Controllable Visit Trajectory Generation with Spatiotemporal Constraints. Haowen Lin, John Krumm, Cyrus Shahabi, Li Xiong |
| 2024 | CounterFair: Group Counterfactuals for Bias Detection, Mitigation and Subgroup Identification. Alejandro Kuratomi, Zed Lee, Panayiotis Tsaparas, Guilherme Dinis Junior, Evaggelia Pitoura, Tony Lindgren, Panagiotis Papapetrou |
| 2024 | Counterfactual Brain Graph Augmentation Guided Bi-Level Contrastive Learning for Disorder Analysis. Guangwei Dong, Xuexiong Luo, Jing Du, Jia Wu, Shan Xue, Jian Yang, Amin Beheshti |
| 2024 | Cross-Store Next-Basket Recommendation. Liang-Chen Ma, Ya Li, Zi-Feng Mai, Fei-Yao Liang, Chang-Dong Wang, Min Chen, Mohsen Guizani |
| 2024 | D-Cube: Exploiting Hyper-Features of Diffusion Model for Robust Medical Classification. Minhee Jang, Juheon Son, Thanaporn Viriyasaranon, Junho Kim, Jang Hwan Choi |
| 2024 | DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning. Kangyang Luo, Shuai Wang, Yexuan Fu, Renrong Shao, Xiang Li, Yunshi Lan, Ming Gao, Jinlong Shu |
| 2024 | DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation. Xiaoshan Yu, Chuan Qin, Qi Zhang, Chen Zhu, Haiping Ma, Xingyi Zhang, Hengshu Zhu |
| 2024 | Debunking Fake News in Online Social Networks Without Text Analysis. Xing Su, Jian Yang, Jia Wu, Zitai Qiu |
| 2024 | Designing an Attack-Defense Game: How to Increase the Robustness of Financial Transaction Models Via a Competition. Alexey Zaytsev, Maria Kovaleva, Alex Natekin, Evgeni Vorsin, Valerii Smirnov, Georgii Smirnov, Oleg Sidorshin, Alexander Senin, Alexander Dudin, Dmitry Berestnev |
| 2024 | DifFaiRec: Generative Fair Recommender with Conditional Diffusion Model. Zhenhao Jiang, Jicong Fan |
| 2024 | Dual Cross-Stage Partial Learning for Detecting Objects in Dehazed Images. JinBiao Zhao, Zhao Zhang, Jiahuan Ren, Haijun Zhang, Zhongqiu Zhao, Meng Wang |
| 2024 | DynoGraph: Dynamic Graph Construction for Nonlinear Dimensionality Reduction. Li Qian, Claudia Plant, Yalan Qin, Jing Qian, Christian Böhm |
| 2024 | EEiF: Efficient Isolated Forest with e Branches for Anomaly Detection. Yifan Zhang, Haolong Xiang, Xuyun Zhang, Xiaolong Xu, Wei Fan, Qin Zhang, Lianyong Qi |
| 2024 | ELiCiT: Effective and Lightweight Lossy Compression of Tensors. Jihoon Ko, Taehyung Kwon, Jinhong Jung, Kijung Shin |
| 2024 | EMIT - Event-Based Masked Auto Encoding for Irregular Time Series. Hrishikesh Patel, Ruihong Qiu, Adam Irwin, Shazia Sadiq, Sen Wang |
| 2024 | Early Fire Detection Based on Local Morphological Knowledge Matching. Xinzhi Wang, Mengyue Li, Nengjun Zhu, Jiayan Qian, Zhanyi Zheng |
| 2024 | Efficient Network Embedding by Approximate Equitable Partitions. Giuseppe Squillace, Mirco Tribastone, Max Tschaikowski, Andrea Vandin |
| 2024 | Efficiently Manipulating Structural Graph Clustering Under Jaccard Similarity. Chuanyu Zong, Rui Fang, Mengxiang Wang, Tao Qiu, Anzhen Zhang |
| 2024 | Emotional Synchronization for Audio-Driven Talking-Head Generation. Zhao Zhang, Yan Luo, Zhichao Zuo, Richang Hong, Yi Yang, Meng Wang |
| 2024 | Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization. Song Wang, Xiaodong Yang, Rashidul Islam, Huiyuan Chen, Minghua Xu, Jundong Li, Yiwei Cai |
| 2024 | Enhancing Embeddings Quality with Stacked Gate for Click-Through Rate Prediction. Caihong Mu, Yunfei Fang, Jialiang Zhou, Yi Liu |
| 2024 | Enhancing Entity Alignment on Probabilistic Knowledge Graphs. Yunfei Li, Lu Chen, Chengfei Liu, Rui Zhou, Jianxin Li |
| 2024 | ExoTST: Exogenous-Aware Temporal Sequence Transformer for Time Series Prediction. Kshitij Tayal, Arvind Renganathan, Xiaowei Jia, Vipin Kumar, Dan Lu |
| 2024 | Exploitation or Exploration Next? User Behavior Decoupling and Emerging Intent Modeling for Next-Item Recommendation. Nengjun Zhu, Lingdan Sun, Xiangfeng Luo, Jian Cao, Qi Zhang, Xinjiang Lu |
| 2024 | Exploratory Combinatorial Optimization Problem Solving via Gauge Transformation. Tianle Pu, Changjun Fan, Mutian Shen, Yizhou Lu, Li Zeng, Zohar Nussinov, Chao Chen, Zhong Liu |
| 2024 | FGLBA: Enabling Highly-Effective and Stealthy Backdoor Attack on Federated Graph Learning. Qing Lu, Miao Hu, Di Wu, Yipeng Zhou, Mohsen Guizani, Quan Z. Sheng |
| 2024 | Fast and Accurate Triangle Counting in Graph Streams Using Predictions. Cristian Boldrin, Fabio Vandin |
| 2024 | Feature Map Purification for Enhancing Adversarial Robustness of Deep Timeseries Classifiers. Mubarak G. Abdu-Aguye, Muhammad Zaigham Zaheer, Karthik Nandakumar |
| 2024 | Financial Risk Assessment via Long-term Payment Behavior Sequence Folding. Yiran Qiao, Yateng Tang, Xiang Ao, Qi Yuan, Ziming Liu, Chen Shen, Xuehao Zheng |
| 2024 | Futures Quantitative Investment With Heterogeneous Continual Graph Neural Network. Zhizhong Tan, Min Hu, Bin Liu, Guosheng Yin |
| 2024 | GADIN: Generative Adversarial Denoise Imputation Network for Incomplete Data. Dong Li, Zhicong Liu, Mingfeng Hu, Baoyan Song, Xiaohuan Shan |
| 2024 | GQ*: Towards Generalizable Deep Q-Learning for Steiner Tree in Graphs. Wei Huang, Hanchen Wang, Dong Wen, Xuefeng Chen, Wenjie Zhang, Ying Zhang |
| 2024 | Generalized Sparse Additive Model with Unknown Link Function. Peipei Yuan, Xinge You, Hong Chen, Xuelin Zhang, Qinmu Peng |
| 2024 | Generating Realistic Tabular Data with Large Language Models. Dang Nguyen, Sunil Gupta, Kien Do, Thin Nguyen, Svetha Venkatesh |
| 2024 | Goal-Guided Generative Prompt Injection Attack on Large Language Models. Chong Zhang, Mingyu Jin, Qinkai Yu, Chengzhi Liu, Haochen Xue, Xiaobo Jin |
| 2024 | Graph Community Augmentation with GMM-Based Modeling in Latent Space. Shintaro Fukushima, Kenji Yamanishi |
| 2024 | Graph Contrastive Learning with Adversarial Structure Refinement (GCL-ASR). Jiangwen Chen, Kou Guang, Huang Yan, Qiyang Li, Tan Hao |
| 2024 | Graph Rhythm Network: Beyond Energy Modeling for Deep Graph Neural Networks. Yufei Jin, Xingquan Zhu |
| 2024 | HFGNN: Efficient Graph Neural Networks Using Hub-Fringe Structures. Pak Lon Ip, Shenghui Zhang, Xuekai Wei, Tsz Nam Chan, Leong Hou U |
| 2024 | Handling Non-IID Data in Federated Learning using Metaheuristic Optimization Techniques. Amin Birashk, Sadaf Md. Halim, Latifur Khan |
| 2024 | Hierarchical Explanations for Text Classification Models: Fast and Effective. Zhenyu Nie, Zheng Xiao, Huizhang Luo, Xuan Liu, Anthony Theodore Chronopoulos |
| 2024 | High-Fidelity Diffusion Editor for Zero-Shot Text-Guided Video Editing. Yan Luo, Zhichao Zuo, Zhao Zhang, Zhongqiu Zhao, Haijun Zhang, Richang Hong |
| 2024 | HomoMGC: Homophily-Enhanced Adaptive Graph Refinement for Multi-View Graph Clustering. Man-Sheng Chen, Xiaosha Cai, Chang-Dong Wang, Dong Huang, Min Chen, Mohsen Guizani |
| 2024 | HyperTime: A Dynamic Hypergraph Approach for Time Series Classification. Raneen Younis, Zahra Ahmadi |
| 2024 | Hypergraph-Enhanced Contrastively Regularized Transformer for Multi-Behavior E-commerce Product Recommendation. Shuiying Liao, P. Y. Mok |
| 2024 | IEEE International Conference on Data Mining, ICDM 2024, Abu Dhabi, United Arab Emirates, December 9-12, 2024 Elena Baralis, Kun Zhang, Ernesto Damiani, Mérouane Debbah, Panos Kalnis, Xindong Wu |
| 2024 | IIFE: Interaction Information Based Automated Feature Engineering. Tom Overman, Diego Klabjan, Jean Utke |
| 2024 | Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder. Duy A. Nguyen, Trang H. Tran, Huy Hieu Pham, Phi Le Nguyen, Lam M. Nguyen |
| 2024 | Influence-Aware Group Recommendation for Social Media Propagation. Chengkun He, Xiangmin Zhou, Chen Wang, Longbing Cao, Jie Shao, Zahir Tari |
| 2024 | Informative Subgraphs Aware Masked Auto-Encoder in Dynamic Graphs. Pengfei Jiao, Xinxun Zhang, Mengzhou Gao, Tianpeng Li, Zhidong Zhao |
| 2024 | Interdependency Matters: Graph Alignment for Multivariate Time Series Anomaly Detection. Yuanyi Wang, Haifeng Sun, Chengsen Wang, Mengde Zhu, Jingyu Wang, Wei Tang, Qi Qi, Zirui Zhuang, Jianxin Liao |
| 2024 | LISA: Learning-Integrated Space Partitioning Framework for Traffic Accident Forecasting on Heterogeneous Spatiotemporal Data. Bang An, Xun Zhou, Amin Vahedian, W. Nick Street, Jinping Guan, Jun Luo |
| 2024 | MOStream: A Modular and Self-Optimizing Data Stream Clustering Algorithm. Zhengru Wang, Xin Wang, Shuhao Zhang |
| 2024 | Margin-Bounded Confidence Scores for Out-of-Distribution Detection. Lakpa Dorje Tamang, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal |
| 2024 | Matrix Profile for Anomaly Detection on Multidimensional Time Series. Chin-Chia Michael Yeh, Audrey Der, Uday Singh Saini, Vivian Lai, Yan Zheng, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Yujie Fan, Huiyuan Chen, Prince Osei Aboagye, Liang Wang, Wei Zhang, Eamonn J. Keogh |
| 2024 | MetaSTC: A Backbone Agnostic Spatio-Temporal Framework for Traffic Forecasting. Kexin Xu, Zhemeng Yu, Yucen Gao, Songjian Zhang, Jun Fang, Xiaofeng Gao, Guihai Chen |
| 2024 | MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model. Alexander Koebler, Ingo Thon, Florian Buettner |
| 2024 | Multi-Hyperbolic Space-Based Heterogeneous Graph Attention Network. Jongmin Park, Seunghoon Han, Jong-Ryul Lee, Sungsu Lim |
| 2024 | Multi-Modal Sarcasm Detection via Dual Synergetic Perception Graph Convolutional Networks. Xingjie Zhuang, Zhixin Li |
| 2024 | Normalizing Self-Supervised Learning for Provably Reliable Change Point Detection. Alexandra Bazarova, Evgenia Romanenkova, Alexey Zaytsev |
| 2024 | PC Zhibin Wang, Jiangtao Cui, Xiyue Gao, Hui Zhang, Guiqi Ren, Yixiao Liu, Hui Li, Kankan Zhao |
| 2024 | PROMIPL: A Probabilistic Generative Model for Multi-Instance Partial-Label Learning. Yin-Fang Yang, Wei Tang, Min-Ling Zhang |
| 2024 | Periodic Prompt on Dynamic Heterogeneous Graph for Next Basket Recommendation. Ru-Bin Li, Man-Sheng Chen, Xin-Yu Ding, Changdong Wang, Sihong Xie, Shuangyin Liu, Min Chen, Mohsen Guizani |
| 2024 | Probabilistic Matrix Factorization-based Three-stage Label Completion for Crowdsourcing. Boyi Yang, Liangxiao Jiang, Wenjun Zhang |
| 2024 | QUCE: The Minimisation and Quantification of Path-Based Uncertainty for Generative Counterfactual Explanations. Jamie Andrew Duell, Monika Seisenberger, Hsuan Fu, Xiuyi Fan |
| 2024 | Rank Supervised Contrastive Learning for Time Series Classification. Qianying Ren, Dongsheng Luo, Dongjin Song |
| 2024 | RecCoder: Reformulating Sequential Recommendation as Large Language Model-Based Code Completion. Kai-Huang Lai, Wu-Dong Xi, Xing-Xing Xing, Wei Wan, Chang-Dong Wang, Min Chen, Mohsen Guizani |
| 2024 | Reducing Unfairness in Distributed Community Detection. Hao Zhang, Malith Jayaweera, Bin Ren, Yanzhi Wang, Sucheta Soundarajan |
| 2024 | Resource2Box: Learning To Rank Resources in Distributed Search Using Box Embedding. Ulugbek Ergashev, Geon Lee, Kijung Shin, Eduard C. Dragut, Weiyi Meng |
| 2024 | SHADE: Deep Density-based Clustering. Anna Beer, Pascal Weber, Lukas Miklautz, Collin Leiber, Walid Durani, Christian Böhm, Claudia Plant |
| 2024 | SR-PredictAO: Session-Based Recommendation with High-Capability Predictor Add-On. Ruida Wang, Raymond Chi-Wing Wong, Weile Tan |
| 2024 | Scalable Graph Classification via Random Walk Fingerprints. Peiyan Li, Honglian Wang, Christian Böhm |
| 2024 | Scalable Order-Preserving Pattern Mining. Ling Li, Wiktor Zuba, Grigorios Loukides, Solon P. Pissis, Maria Matsangidou |
| 2024 | Scaling Disk Failure Prediction via Multi-Source Stream Mining. Shujie Han, Zirui Ou, Qun Huang, Patrick P. C. Lee |
| 2024 | SemiFDA: Domain Adaptation in Semi-Supervised Federated Learning. Michele Craighero, Giorgio Rossi, Beatrice Rossi, Diego Carrera, Diego Stucchi, Pasqualina Fragneto, Giacomo Boracchi |
| 2024 | Solving Combinatorial Optimization Problem Over Graph Through QUBO Transformation and Deep Reinforcement Learning. Tianle Pu, Chao Chen, Li Zeng, Shixuan Liu, Rui Sun, Changjun Fan |
| 2024 | SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning. Rikuto Kotoge, Zheng Chen, Tasuku Kimura, Yasuko Matsubara, Takufumi Yanagisawa, Haruhiko Kishima, Yasushi Sakurai |
| 2024 | Survival Analysis with Multiple Noisy Labels. Donna Tjandra, Jenna Wiens |
| 2024 | TAN: A Tripartite Alignment Network Enhancing Composed Image Retrieval with Momentum Distillation. Yongquan Wan, Erhe Yang, Cairong Yan, Guobing Zou, Bofeng Zhang |
| 2024 | TROPICAL: Transformer-Based Hypergraph Learning for Camouflaged Fraudster Detection. Venus Haghighi, Behnaz Soltani, Nasrin Shabani, Jia Wu, Yang Zhang, Lina Yao, Quan Z. Sheng, Jian Yang |
| 2024 | Towards Cross-Domain Few-Shot Graph Anomaly Detection. Jiazhen Chen, Sichao Fu, Zhibin Zhang, Zheng Ma, Mingbin Feng, Tony S. Wirjanto, Qinmu Peng |
| 2024 | Towards Dynamic University Course Timetabling Problem: An Automated Approach Augmented via Reinforcement Learning. Yanan Xiao, Xianglin Li, Lu Jiang, Pengfei Wang, Kaidi Wang, Na Luo |
| 2024 | Towards Efficient Ridesharing via Order-Vehicle Pre-Matching Using Attention Mechanism. Zhidan Liu, Jinye Lin, Zhiyu Xia, Chao Chen, Kaishun Wu |
| 2024 | Towards Expressive Graph Representations for Graph Neural Networks. Chengsheng Mao, Liang Yao, Yuan Luo |
| 2024 | Traffic Pattern Sharing for Federated Traffic Flow Prediction with Personalization. Hang Zhou, Wentao Yu, Sheng Wan, Yongxin Tong, Tianlong Gu, Chen Gong |
| 2024 | Transitivity-Encoded Graph Attention Networks for Complementary Item Recommendations. Jin Shang, Yang Jiao, Chenghuan Guo, Minghao Sun, Yan Gao, Jia Liu, Michinari Momma, Itetsu Taru, Yi Sun |
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| 2024 | Utilitarian Online Learning from Open-World Soft Sensing. Heng Lian, Yu Huang, Xingquan Zhu, Yi He |
| 2024 | Warm-Starting Contextual Bandits Under Latent Reward Scaling. Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein |
| 2024 | Weakly-Supervised Graph Classification with Even a Single Key Subgraph Per Class. Lu Zhang, Chenbo Zhang, Jihong Guan, Shuigeng Zhou |
| 2024 | Zero-Shot Link Prediction in Knowledge Graphs with Large Language Models. Mingchen Li, Chen Ling, Rui Zhang, Liang Zhao |