| 2023 | Universal Agent Mixtures and the Geometry of Intelligence. | Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter |
| 2023 | Learning Robust Graph Neural Networks with Limited Supervision. | Abdullah Alchihabi, Yuhong Guo |
| 2023 | Adapting to Latent Subgroup Shifts via Concepts and Proxies. | Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai |
| 2023 | Conformalized Unconditional Quantile Regression. | Ahmed M. Alaa, Zeshan M. Hussain, David A. Sontag |
| 2023 | Probing Graph Representations. | Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski |
| 2023 | Generative Oversampling for Imbalanced Data via Majority-Guided VAE. | Qingzhong Ai, Pengyun Wang, Lirong He, Liangjian Wen, Lujia Pan, Zenglin Xu |
| 2023 | Semantic Strengthening of Neuro-Symbolic Learning. | Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck |
| 2023 | Improved Approximation for Fair Correlation Clustering. | Sara Ahmadian, Maryam Negahbani |
| 2023 | On the bias of K-fold cross validation with stable learners. | Anass Aghbalou, Anne Sabourin, Franois Portier |
| 2023 | Discrete Distribution Estimation under User-level Local Differential Privacy. | Jayadev Acharya, Yuhan Liu, Ziteng Sun |
| 2023 | Sample Complexity of Distinguishing Cause from Effect. | Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun |
| 2023 | Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games. | Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki |
| 2023 | Federated Asymptotics: a model to compare federated learning algorithms. | Gary Cheng, Karan N. Chadha, John C. Duchi |
| 2023 | A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization. | Yutong Dai, Guanyi Wang, Frank E. Curtis, Daniel P. Robinson |
| 2023 | Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions. | Kaiqi Zhao, Animesh Jain, Ming Zhao |
| 2023 | Blessing of Class Diversity in Pre-training. | Yulai Zhao, Jianshu Chen, Simon S. Du |
| 2023 | Near-Optimal Differentially Private Reinforcement Learning. | Dan Qiao, Yu-Xiang Wang |
| 2023 | A New Causal Decomposition Paradigm towards Health Equity. | Xinwei Sun, Xiangyu Zheng, Jim Weinstein |
| 2023 | Nonparametric Gaussian Process Covariances via Multidimensional Convolutions. | Thomas M. McDonald, Magnus Ross, Michael T. Smith, Mauricio A. lvarez |
| 2023 | Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification. | Yuqing Hu, Stphane Pateux, Vincent Gripon |
| 2023 | Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets. | Hussein Hazimeh, Natalia Ponomareva |
| 2023 | Boosted Off-Policy Learning. | Ben London, Levi Lu, Ted Sandler, Thorsten Joachims |
| 2023 | Benign overfitting of non-smooth neural networks beyond lazy training. | Xingyu Xu, Yuantao Gu |
| 2023 | Oblivious near-optimal sampling for multidimensional signals with Fourier constraints. | Xingyu Xu, Yuantao Gu |
| 2023 | Deep Neural Networks with Efficient Guaranteed Invariances. | Matthias Rath, Alexandru Paul Condurache |