| 2024 | Invariant Aggregator for Defending against Federated Backdoor Attacks. | Xiaoyang Wang, Dimitrios Dimitriadis, Sanmi Koyejo, Shruti Tople |
| 2024 | On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information Asymmetry. | Serena Wang, Stephen Bates, P. M. Aronow, Michael I. Jordan |
| 2024 | Model-based Policy Optimization under Approximate Bayesian Inference. | Chaoqi Wang, Yuxin Chen, Kevin Murphy |
| 2024 | On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective. | Yipei Wang, Xiaoqian Wang |
| 2024 | Interpretability Guarantees with Merlin-Arthur Classifiers. | Stephan Wldchen, Kartikey Sharma, Berkant Turan, Max Zimmer, Sebastian Pokutta |
| 2024 | Diagonalisation SGD: Fast & Convergent SGD for Non-Differentiable Models via Reparameterisation and Smoothing. | Dominik Wagner, Basim Khajwal, Luke Ong |
| 2024 | Analysis of Privacy Leakage in Federated Large Language Models. | Minh N. Vu, Truc D. T. Nguyen, Tre' R. Jeter, My T. Thai |
| 2024 | Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements. | Emmanouil-Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie |
| 2024 | Taming False Positives in Out-of-Distribution Detection with Human Feedback. | Harit Vishwakarma, Heguang Lin, Ramya Korlakai Vinayak |
| 2024 | Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers. | Matteo Vilucchio, Emanuele Troiani, Vittorio Erba, Florent Krzakala |
| 2024 | Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. | Paul Viallard, Rmi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi |
| 2024 | Variational Gaussian Process Diffusion Processes. | Prakhar Verma, Vincent Adam, Arno Solin |
| 2024 | Optimal Budgeted Rejection Sampling for Generative Models. | Alexandre Verine, Muni Sreenivas Pydi, Benjamin Ngrevergne, Yann Chevaleyre |
| 2024 | Learning Sparse Codes with Entropy-Based ELBOs. | Dmytro Velychko, Simon Damm, Asja Fischer, Jrg Lcke |
| 2024 | Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs. | Mishfad Shaikh Veedu, Deepjyoti Deka, Murti V. Salapaka |
| 2024 | General Identifiability and Achievability for Causal Representation Learning. | Burak Varici, Emre Acartrk, Karthikeyan Shanmugam, Ali Tajer |
| 2024 | Ordinal Potential-based Player Rating. | Nelson Vadori, Rahul Savani |
| 2024 | Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains. | Nikita Tsoy, Anna Mihalkova, Teodora N. Todorova, Nikola Konstantinov |
| 2024 | Manifold-Aligned Counterfactual Explanations for Neural Networks. | Asterios Tsiourvas, Wei Sun, Georgia Perakis |
| 2024 | Proxy Methods for Domain Adaptation. | Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou, Matt J. Kusner, Alexander D'Amour, Sanmi Koyejo, Arthur Gretton |
| 2024 | Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging. | Chung-En Tsai, Hao-Chung Cheng, Yen-Huan Li |
| 2024 | Sequence Length Independent Norm-Based Generalization Bounds for Transformers. | Jacob Trauger, Ambuj Tewari |
| 2024 | E(3)-Equivariant Mesh Neural Networks. | Thuan Anh Trang, Nhat Khang Ngo, Daniel Levy, Ngoc Thieu Vo, Siamak Ravanbakhsh, Truong Son Hy |
| 2024 | LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object Detection. | Phi Vu Tran |
| 2024 | Scalable Meta-Learning with Gaussian Processes. | Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp |