| 2023 | But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI. | Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan |
| 2023 | Federated Learning for Data Streams. | Othmane Marfoq, Giovanni Neglia, Laetitia Kameni, Richard Vidal |
| 2023 | Equivariant Representation Learning via Class-Pose Decomposition. | Giovanni Luca Marchetti, Gustaf Tegnr, Anastasiia Varava, Danica Kragic |
| 2023 | An Efficient and Continuous Voronoi Density Estimator. | Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic |
| 2023 | High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. | Paul Mangold, Aurlien Bellet, Joseph Salmon, Marc Tommasi |
| 2023 | Heavy Sets with Applications to Interpretable Machine Learning Diagnostics. | Dmitry M. Malioutov, Sanjeeb Dash, Dennis Wei |
| 2023 | Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. | Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff |
| 2023 | Optimal Sketching Bounds for Sparse Linear Regression. | Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff |
| 2023 | Efficient SAGE Estimation via Causal Structure Learning. | Christoph Luther, Gunnar Knig, Moritz Grosse-Wentrup |
| 2023 | Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity. | Xingyu Lu, Hasin Us Sami, Basak Gler |
| 2023 | Improved Rate of First Order Algorithms for Entropic Optimal Transport. | Yiling Luo, Yiling Xie, Xiaoming Huo |
| 2023 | Model-Based Uncertainty in Value Functions. | Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters |
| 2023 | Private Non-Convex Federated Learning Without a Trusted Server. | Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn |
| 2023 | Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints. | Kyriakos Lotidis, Nicholas Bambos, Jose H. Blanchet, Jiajin Li |
| 2023 | A Sea of Words: An In-Depth Analysis of Anchors for Text Data. | Gianluigi Lopardo, Frdric Precioso, Damien Garreau |
| 2023 | A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning. | Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan |
| 2023 | Meta-Learning with Adjoint Methods. | Shibo Li, Zheng Wang, Akil Narayan, Robert M. Kirby, Shandian Zhe |
| 2023 | Inducing Neural Collapse in Deep Long-tailed Learning. | Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Yuan Yao, Lujia Pan |
| 2023 | INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation. | Ning Liu, Yue Yu, Huaiqian You, Neeraj Tatikola |
| 2023 | Adaptation to Misspecified Kernel Regularity in Kernelised Bandits. | Yusha Liu, Aarti Singh |
| 2023 | Nonstationary Bandit Learning via Predictive Sampling. | Yueyang Liu, Benjamin Van Roy, Kuang Xu |
| 2023 | EEGNN: Edge Enhanced Graph Neural Network with a Bayesian Nonparametric Graph Model. | Yirui Liu, Xinghao Qiao, Liying Wang, Jessica Lam |
| 2023 | ForestPrune: Compact Depth-Pruned Tree Ensembles. | Brian Liu, Rahul Mazumder |
| 2023 | Sparse Bayesian optimization. | Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy |
| 2023 | Consistent Complementary-Label Learning via Order-Preserving Losses. | Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An |