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| 2024 | Deep Efficient Private Neighbor Generation for Subgraph Federated Learning. Ke Zhang, Lichao Sun, Bolin Ding, Siu Ming Yiu, Carl Yang |
| 2024 | Denoising Long- and Short-term Interests for Sequential Recommendation. Xinyu Zhang, Beibei Li, Beihong Jin |
| 2024 | Differences Between Hard and Noisy-labeled Samples: An Empirical Study. Mahsa Forouzesh, Patrick Thiran |
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| 2024 | Dimensionality-Aware Outlier Detection. Alastair Anderberg, James Bailey, Ricardo J. G. B. Campello, Michael E. Houle, Henrique O. Marques, Milos Radovanovic, Arthur Zimek |
| 2024 | Disinformation Detection: An Evolving Challenge in the Age of LLMs. Bohan Jiang, Zhen Tan, Ayushi Nirmal, Huan Liu |
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| 2024 | Foundation Models for Spatiotemporal Tasks in the Physical World. Zhe Jiang, Yu Wang, Zelin Xu |
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| 2024 | Graph-based Student Knowledge Profile for Online Intelligent Education. Jinze Wu, Haotian Zhang, Zhenya Huang, Liang Ding, Qi Liu, Jing Sha, Enhong Chen, Shijin Wang |
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| 2024 | Helper Recommendation with seniority control in Online Health Community. Junruo Gao, Chen Ling, Carl Yang, Liang Zhao |
| 2024 | HyperFLoRA: Federated Learning with Instantaneous Personalization. Qikai Lu, Di Niu, Mohammadamin Samadi Khoshkho, Baochun Li |
| 2024 | Identification and Uses of Deep Learning Backbones via Pattern Mining. Michael J. Livanos, Ian Davidson |
| 2024 | Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features. Erhu He, Yiqun Xie, Licheng Liu, Zhenong Jin, Dajun Zhang, Xiaowei Jia |
| 2024 | Label Distribution Learning-Enhanced Dual-KNN for Text Classification. Bo Yuan, Yulin Chen, Zhen Tan, Jinyan Wang, Huan Liu, Yin Zhang |
| 2024 | Laplacian Score Benefit Adaptive Filter Selection for Graph Neural Networks. Yewen Wang, Shichang Zhang, John (Junghoo) Cho, Yizhou Sun |
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| 2024 | Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu |
| 2024 | MISS: Multiclass Interpretable Scoring Systems. Michal K. Grzeszczyk, Tomasz Trzcinski, Arkadiusz Sitek |
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| 2024 | Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling. Shaoming Xu, Ankush Khandelwal, Arvind Renganathan, Vipin Kumar |
| 2024 | Meta-Adaptive Stock Movement Prediction with Two-Stage Representation Learning. Donglin Zhan, Yusheng Dai, Yiwei Dong, Jinghai He, Zhenyi Wang, James Anderson |
| 2024 | Multi-Interest Network with Simple Diffusion for Multi-Behavior Sequential Recommendation. Qingfeng Li, Huifang Ma, Wangyu Jin, Yugang Ji, Zhixin Li |
| 2024 | Multi-polytope Machine for Classification. Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam, Chandra Reddy |
| 2024 | MultiNetAD: Multiplex Network-Based Anomaly Access Detection Featuring Semantic Hierarchies. Ziqi Yuan, Qingyun Sun, Haoyi Zhou, Zukun Zhu, Jianxin Li |
| 2024 | Neural Locality Sensitive Hashing for Entity Blocking. Runhui Wang, Luyang Kong, Yefan Tao, Andrew Borthwick, Davor Golac, Henrik Johnson, Shadie Hijazi, Dong Deng, Yongfeng Zhang |
| 2024 | Non-Euclidean Spatial Graph Neural Network. Zheng Zhang, Sirui Li, Jingcheng Zhou, Junxiang Wang, Abhinav Angirekula, Allen Zhang, Liang Zhao |
| 2024 | On Robust Wasserstein Barycenter: The Model and Algorithm. Xu Wang, Jiawei Huang, Qingyuan Yang, Jinpeng Zhang |
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| 2024 | Only Attending What Matter within Trajectories - Mingzhi Hu, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo |
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| 2024 | Pattern-based Time Series Semantic Segmentation with Gradual State Transitions. Louis Carpentier, Len Feremans, Wannes Meert, Mathias Verbeke |
| 2024 | Personalized Federated Learning with Contextual Modulation and Meta-Learning. Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson |
| 2024 | Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management. Somya Sharma Chatterjee, Kelly Lindsay, Neel Chatterjee, Rohan Patil, Ilkay Altintas De Callafon, Michael S. Steinbach, Daniel Giron, Mai H. Nguyen, Vipin Kumar |
| 2024 | Pretraining Molecules with Explicit Substructure Information. Yuting Ma, Shuo Yu, Yanming Shen |
| 2024 | Proceedings of the 2024 SIAM International Conference on Data Mining, SDM 2024, Houston, TX, USA, April 18-20, 2024 Shashi Shekhar, Vagelis Papalexakis, Jing Gao, Zhe Jiang, Matteo Riondato |
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| 2024 | RHINE: A Regime-Switching Model with Nonlinear Representation for Discovering and Forecasting Regimes in Financial Markets. Kunpeng Xu, Lifei Chen, Jean-Marc Patenaude, Shengrui Wang |
| 2024 | Refining Pre-trained Language Models for Domain Adaptation with Entity-Aware Discriminative and Contrastive Learning. Jian Yang, Xinyu Hu, Yulong Shen, Gang Xiao |
| 2024 | Robust Estimation of Causal Heteroscedastic Noise Models. Quang-Duy Tran, Bao Duong, Phuoc Nguyen, Thin Nguyen |
| 2024 | Robust Sparse Online Learning for Data Streams with Streaming Features. Zhong Chen, Yi He, Di Wu, Huixin Zhan, Victor S. Sheng, Kun Zhang |
| 2024 | STES: A Spatiotemporal Explanation Supervision Framework. Dazhou Yu, Binbin Chen, Yun Li, Suman Dhakal, Yifei Zhang, Zhenke Liu, Minxing Zhang, Jie Zhang, Liang Zhao |
| 2024 | Self-Similar Graph Neural Network for Hierarchical Graph Learning. Zheng Zhang, Liang Zhao |
| 2024 | Semi-Supervised Clustering via Structural Entropy with Different Constraints. Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Runze Yang, Chunyang Liu, Lifang He |
| 2024 | Semi-Supervised Isolation Forest for Anomaly Detection. Luca Stradiotti, Lorenzo Perini, Jesse Davis |
| 2024 | Spatial-Aware Deep Reinforcement Learning for the Traveling Officer Problem. Niklas Strauß, Matthias Schubert |
| 2024 | Spatial-Temporal Augmented Adaptation via Cycle-Consistent Adversarial Network: An Application in Streamflow Prediction. Nasrin Kalanat, Yiqun Xie, Yanhua Li, Xiaowei Jia |
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| 2024 | Tensorized Hypergraph Neural Networks. Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao |
| 2024 | Test-Time Training for Spatial-Temporal Forecasting. Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang |
| 2024 | Time-Transformer: Integrating Local and Global Features for Better Time Series Generation. Yuansan Liu, Sudanthi N. R. Wijewickrema, Ang Li, Christofer Bester, Stephen J. O'Leary, James Bailey |
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