| 2024 | Generative Flow Networks as Entropy-Regularized RL. | Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry P. Vetrov |
| 2024 | Contextual Directed Acyclic Graphs. | Ryan Thompson, Edwin V. Bonilla, Robert Kohn |
| 2024 | Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean. | Anton Frederik Thielmann, Ren-Marcel Kruse, Thomas Kneib, Benjamin Sfken |
| 2024 | Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. | Jrn Tebbe, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann, Fabian Mies |
| 2024 | Learning Populations of Preferences via Pairwise Comparison Queries. | Gokcan Tatli, Yi Chen, Ramya Korlakai Vinayak |
| 2024 | Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods. | Davoud Ataee Tarzanagh, Parvin Nazari, Bojian Hou, Li Shen, Laura Balzano |
| 2024 | Quantifying Uncertainty in Natural Language Explanations of Large Language Models. | Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju |
| 2024 | Adaptivity of Diffusion Models to Manifold Structures. | Rong Tang, Yun Yang |
| 2024 | Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint. | Haoyue Tang, Tian Xie, Aosong Feng, Hanyu Wang, Chenyang Zhang, Yang Bai |
| 2024 | Stochastic Multi-Armed Bandits with Strongly Reward-Dependent Delays. | Yifu Tang, Yingfei Wang, Zeyu Zheng |
| 2024 | Informative Path Planning with Limited Adaptivity. | Rayen Tan, Rohan Ghuge, Viswanath Nagarajan |
| 2024 | Data-Driven Confidence Intervals with Optimal Rates for the Mean of Heavy-Tailed Distributions. | Ambrus Tams, Szabolcs Szentpteri, Balzs Csand Csji |
| 2024 | Model-Based Best Arm Identification for Decreasing Bandits. | Sho Takemori, Yuhei Umeda, Aditya Gopalan |
| 2024 | Learning to Defer to a Population: A Meta-Learning Approach. | Dharmesh Tailor, Aditya Patra, Rajeev Verma, Putra Manggala, Eric T. Nalisnick |
| 2024 | Understanding Progressive Training Through the Framework of Randomized Coordinate Descent. | Rafal Szlendak, Elnur Gasanov, Peter Richtrik |
| 2024 | Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems. | Wesley Suttle, Vipul Kumar Sharma, Krishna Chaitanya Kosaraju, Seetharaman Sivaranjani, Ji Liu, Vijay Gupta, Brian M. Sadler |
| 2024 | Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters. | Zhenyu Sun, Xiaochun Niu, Ermin Wei |
| 2024 | Sparse and Faithful Explanations Without Sparse Models. | Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin |
| 2024 | MINTY: Rule-based models that minimize the need for imputing features with missing values. | Lena Stempfle, Fredrik D. Johansson |
| 2024 | Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity. | Vincent Souveton, Arnaud Guillin, Jens Jasche, Guilhem Lavaux, Manon Michel |
| 2024 | Optimising Distributions with Natural Gradient Surrogates. | Jonathan So, Richard E. Turner |
| 2024 | Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes. | Jinwon Sohn, Qifan Song, Guang Lin |
| 2024 | Making Better Use of Unlabelled Data in Bayesian Active Learning. | Freddie Bickford Smith, Adam Foster, Tom Rainforth |
| 2024 | Online Distribution Learning with Local Privacy Constraints. | Jin Sima, Changlong Wu, Olgica Milenkovic, Wojciech Szpankowski |
| 2024 | DiffRed: Dimensionality reduction guided by stable rank. | Prarabdh Shukla, Gagan Raj Gupta, Kunal Dutta |