| 2023 | Graph Spectral Embedding using the Geodesic Betweenness Centrality. | Shay Deutsch, Stefano Soatto |
| 2023 | Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings. | Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson |
| 2023 | Reinforcement Learning with Stepwise Fairness Constraints. | Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes |
| 2023 | MMD-B-Fair: Learning Fair Representations with Statistical Testing. | Namrata Deka, Danica J. Sutherland |
| 2023 | Transport Reversible Jump Proposals. | Laurence Davies, Robert Salomone, Matthew Sutton, Chris Drovandi |
| 2023 | Multiple-policy High-confidence Policy Evaluation. | Christoph Dann, Mohammad Ghavamzadeh, Teodor V. Marinov |
| 2023 | The ELBO of Variational Autoencoders Converges to a Sum of Entropies. | Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jrg Lcke |
| 2023 | Learning to Optimize with Stochastic Dominance Constraints. | Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai |
| 2023 | Fast Variational Estimation of Mutual Information for Implicit and Explicit Likelihood Models. | Caleb Dahlke, Sue Zheng, Jason Pacheco |
| 2023 | Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data. | Alicia Curth, Mihaela van der Schaar |
| 2023 | Actually Sparse Variational Gaussian Processes. | Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth |
| 2023 | Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover. | Victoria G. Crawford |
| 2023 | Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare. | Cyrus Cousins |
| 2023 | Neural Simulated Annealing. | Alvaro H. C. Correia, Daniel E. Worrall, Roberto Bondesan |
| 2023 | Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. | Weilin Cong, Mehrdad Mahdavi |
| 2023 | Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier. | Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan H. Greenewald, Murat Kocaoglu |
| 2023 | On double-descent in uncertainty quantification in overparametrized models. | Lucas Clart, Bruno Loureiro, Florent Krzakala, Lenka Zdeborov |
| 2023 | One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning. | Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar |
| 2023 | Variational Boosted Soft Trees. | Tristan Cinquin, Tammo Rukat, Philipp Schmidt, Martin Wistuba, Artur Bekasov |
| 2023 | Provable Hierarchy-Based Meta-Reinforcement Learning. | Kurtland Chua, Qi Lei, Jason D. Lee |
| 2023 | Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems. | Nicolas Christianson, Junxuan Shen, Adam Wierman |
| 2023 | Subset verification and search algorithms for causal DAGs. | Davin Choo, Kirankumar Shiragur |
| 2023 | Approximating a RUM from Distributions on k-Slates. | Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins |
| 2023 | Byzantine-Robust Online and Offline Distributed Reinforcement Learning. | Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu |
| 2023 | On-Demand Communication for Asynchronous Multi-Agent Bandits. | Yu-Zhen Janice Chen, Lin Yang, Xuchuang Wang, Xutong Liu, Mohammad H. Hajiesmaili, John C. S. Lui, Don Towsley |