| 2025 | Conditional Average Treatment Effect Estimation Under Hidden Confounders. | Ahmed Aloui, Juncheng Dong, Ali Hasan, Vahid Tarokh |
| 2025 | Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information. | mer Faruk Akgl, Rajgopal Kannan, Viktor K. Prasanna |
| 2025 | Causal Inference amid Missingness-Specific Independences and Mechanism Shifts. | Johan de Aguas, Leonard Henckel, Johan Pensar, Guido Biele |
| 2025 | Aggregating Data for Optimal Learning. | Sushant Agarwal, Yukti Makhija, Rishi Saket, Aravindan Raghuveer |
| 2024 | Approximate Kernel Density Estimation under Metric-based Local Differential Privacy. | Yi Zhou, Yanhao Wang, Long Teng, Qiang Huang, Cen Chen |
| 2024 | Trusted re-weighting for label distribution learning. | Zhuoran Zheng, Chen Wu, Yeying Jin, Xiuyi Jia |
| 2024 | Exploring High-dimensional Search Space via Voronoi Graph Traversing. | Aidong Zhao, Xuyang Zhao, Tianchen Gu, Zhaori Bi, Xinwei Sun, Changhao Yan, Fan Yang, Dian Zhou, Xuan Zeng |
| 2024 | Partial Identification with Proxy of Latent Confoundings via Sum-of-ratios Fractional Programming. | Zhiheng Zhang, Xinyan Su |
| 2024 | Neighbor Similarity and Multimodal Alignment based Product Recommendation Study. | Zhiqiang Zhang, Yongqiang Jiang, Qian Gao, Zhipeng Wang |
| 2024 | Decentralized Two-Sided Bandit Learning in Matching Market. | Yirui Zhang, Zhixuan Fang |
| 2024 | Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem. | Cong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jing Sun |
| 2024 | Causally Abstracted Multi-armed Bandits. | Fabio Massimo Zennaro, Nicholas Bishop, Joel Dyer, Yorgos Felekis, Anisoara Calinescu, Michael J. Wooldridge, Theodoros Damoulas |
| 2024 | Dirichlet Continual Learning: Tackling Catastrophic Forgetting in NLP. | Min Zeng, Haiqin Yang, Wei Xue, Qifeng Liu, Yike Guo |
| 2024 | Probabilistic reconciliation of mixed-type hierarchical time series. | Lorenzo Zambon, Dario Azzimonti, Nicol Rubattu, Giorgio Corani |
| 2024 | Offline Reward Perturbation Boosts Distributional Shift in Online RL. | Zishun Yu, Siteng Kang, Xinhua Zhang |
| 2024 | Decentralized Online Learning in General-Sum Stackelberg Games. | Yaolong Yu, Haipeng Chen |
| 2024 | Domain Adaptation with Cauchy-Schwarz Divergence. | Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu, Jan-Jakob Sonke, Efstratios Gavves |
| 2024 | On Hardware-efficient Inference in Probabilistic Circuits. | Lingyun Yao, Martin Trapp, Jelin Leslin, Gaurav Singh, Peng Zhang, Karthekeyan Periasamy, Martin Andraud |
| 2024 | Masking the Unknown: Leveraging Masked Samples for Enhanced Data Augmentation. | Xun Yao, Zijian Huang, Xinrong Hu, Jie Yang, Yi Guo |
| 2024 | Graph Contrastive Learning under Heterophily via Graph Filters. | Wenhan Yang, Baharan Mirzasoleiman |
| 2024 | Statistical and Causal Robustness for Causal Null Hypothesis Tests. | Junhui Yang, Rohit Bhattacharya, Youjin Lee, Ted Westling |
| 2024 | Base Models for Parabolic Partial Differential Equations. | Xingzi Xu, Ali Hasan, Jie Ding, Vahid Tarokh |
| 2024 | Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise. | Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman |
| 2024 | Functional Wasserstein Variational Policy Optimization. | Junyu Xuan, Mengjing Wu, Zihe Liu, Jie Lu |
| 2024 | α-Former: Local-Feature-Aware (L-FA) Transformer. | Zhi Xu, Bin Sun, Yue Bai, Yun Fu |