| 2024 | Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. | Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi |
| 2024 | Unified Training of Universal Time Series Forecasting Transformers. | Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo |
| 2024 | Coresets for Multiple ℓp Regression. | David P. Woodruff, Taisuke Yasuda |
| 2024 | Reweighted Solutions for Weighted Low Rank Approximation. | David P. Woodruff, Taisuke Yasuda |
| 2024 | Expressivity and Generalization: Fragment-Biases for Molecular GNNs. | Tom Wollschlger, Niklas Kemper, Leon Hetzel, Johanna Sommer, Stephan Gnnemann |
| 2024 | Fundamental Limitations of Alignment in Large Language Models. | Yotam Wolf, Noam Wies, Oshri Avnery, Yoav Levine, Amnon Shashua |
| 2024 | Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem. | Maciej Wolczyk, Bartlomiej Cupial, Mateusz Ostaszewski, Michal Bortkiewicz, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos |
| 2024 | Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models. | Ludwig Winkler, Lorenz Richter, Manfred Opper |
| 2024 | A Distributional Analogue to the Successor Representation. | Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, Andr Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland |
| 2024 | Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains. | Steven Wilkins-Reeves, Xu Chen, Qi Ma, Christine Agarwal, Aude Hofleitner |
| 2024 | QuRating: Selecting High-Quality Data for Training Language Models. | Alexander Wettig, Aatmik Gupta, Saumya Malik, Danqi Chen |
| 2024 | Stability-Informed Initialization of Neural Ordinary Differential Equations. | Theodor Westny, Arman Mohammadi, Daniel Jung, Erik Frisk |
| 2024 | On the Asymptotic Distribution of the Minimum Empirical Risk. | Jacob Westerhout, TrungTin Nguyen, Xin Guo, Hien Duy Nguyen |
| 2024 | Provable Contrastive Continual Learning. | Yichen Wen, Zhiquan Tan, Kaipeng Zheng, Chuanlong Xie, Weiran Huang |
| 2024 | Distributional Bellman Operators over Mean Embeddings. | Li Kevin Wenliang, Grgoire Deltang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland |
| 2024 | From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble. | Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, Yanfang Ye |
| 2024 | Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning. | Yuxiao Wen, Arthur Jacot |
| 2024 | Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning. | Xiaoyu Wen, Chenjia Bai, Kang Xu, Xudong Yu, Yang Zhang, Xuelong Li, Zhen Wang |
| 2024 | Cross-domain Open-world Discovery. | Shuo Wen, Maria Brbic |
| 2024 | Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems. | Siwei Wei, Xudong Zhang, Zhiyang Zhou, Yan Cai |
| 2024 | SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning. | Matthias Weissenbacher, Rishabh Agarwal, Yoshinobu Kawahara |
| 2024 | Position: AI/ML Influencers Have a Place in the Academic Process. | Iain Weissburg, Mehir Arora, Xinyi Wang, Liangming Pan, William Yang Wang |
| 2024 | Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. | Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson |
| 2024 | Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-trained Models. | Yongxian Wei, Zixuan Hu, Li Shen, Zhenyi Wang, Yu Li, Chun Yuan, Dacheng Tao |
| 2024 | Rethinking Generative Large Language Model Evaluation for Semantic Comprehension. | Fangyun Wei, Xi Chen, Lin Luo |