| 2024 | Breaking isometric ties and introducing priors in Gromov-Wasserstein distances. | Pinar Demetci, Quang Huy Tran, Ievgen Redko, Ritambhara Singh |
| 2024 | Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources. | Rohan Deb, Aadirupa Saha, Arindam Banerjee |
| 2024 | Emergent specialization from participation dynamics and multi-learner retraining. | Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel |
| 2024 | Data-Driven Online Model Selection With Regret Guarantees. | Christoph Dann, Claudio Gentile, Aldo Pacchiano |
| 2024 | Graph Partitioning with a Move Budget. | Mina Dalirrooyfard, Elaheh Fata, Majid Behbahani, Yuriy Nevmyvaka |
| 2024 | Local Causal Discovery with Linear non-Gaussian Cyclic Models. | Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang |
| 2024 | SADI: Similarity-Aware Diffusion Model-Based Imputation for Incomplete Temporal EHR Data. | Zongyu Dai, Emily J. Getzen, Qi Long |
| 2024 | Can Probabilistic Feedback Drive User Impacts in Online Platforms? | Jessica Dai, Bailey Flanigan, Meena Jagadeesan, Nika Haghtalab, Chara Podimata |
| 2024 | A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization. | Mathieu Dagrou, Thomas Moreau, Samuel Vaiter, Pierre Ablin |
| 2024 | Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients. | Chris Cundy, Rishi Desai, Stefano Ermon |
| 2024 | Theory-guided Message Passing Neural Network for Probabilistic Inference. | Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji |
| 2024 | Robust Non-linear Normalization of Heterogeneous Feature Distributions with Adaptive Tanh-Estimators. | Felip Guimer Cuevas, Helmut Schmid |
| 2024 | Sequential learning of the Pareto front for multi-objective bandits. | lise Crepon, Aurlien Garivier, Wouter M. Koolen |
| 2024 | To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models. | Cyrus Cousins, I. Elizabeth Kumar, Suresh Venkatasubramanian |
| 2024 | A Unifying Variational Framework for Gaussian Process Motion Planning. | Lucas Cosier, Rares Iordan, Sicelukwanda N. T. Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu |
| 2024 | SDEs for Minimax Optimization. | Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Proske, Aurlien Lucchi |
| 2024 | Differentially Private Reward Estimation with Preference Feedback. | Sayak Ray Chowdhury, Xingyu Zhou, Nagarajan Natarajan |
| 2024 | Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers. | Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tams Sarls, Thomas Weingarten, Adrian Weller |
| 2024 | Causal Discovery under Off-Target Interventions. | Davin Choo, Kirankumar Shiragur, Caroline Uhler |
| 2024 | An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization. | Lesi Chen, Haishan Ye, Luo Luo |
| 2024 | Lower-level Duality Based Reformulation and Majorization Minimization Algorithm for Hyperparameter Optimization. | He Chen, Haochen Xu, Rujun Jiang, Anthony Man-Cho So |
| 2024 | Gibbs-Based Information Criteria and the Over-Parameterized Regime. | Haobo Chen, Gregory W. Wornell, Yuheng Bu |
| 2024 | Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression. | Sijin Chen, Zhize Li, Yuejie Chi |
| 2024 | Provable Policy Gradient Methods for Average-Reward Markov Potential Games. | Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian |
| 2024 | Non-Convex Joint Community Detection and Group Synchronization via Generalized Power Method. | Sijin Chen, Xiwei Cheng, Anthony Man-Cho So |