| 2023 | Compositional Probabilistic and Causal Inference using Tractable Circuit Models. | Benjie Wang, Marta Kwiatkowska |
| 2023 | Incremental Aggregated Riemannian Gradient Method for Distributed PCA. | Xiaolu Wang, Yuchen Jiao, Hoi-To Wai, Yuantao Gu |
| 2023 | Data Banzhaf: A Robust Data Valuation Framework for Machine Learning. | Jiachen T. Wang, Ruoxi Jia |
| 2023 | Probabilistic Conformal Prediction Using Conditional Random Samples. | Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei |
| 2023 | LOFT: Finding Lottery Tickets through Filter-wise Training. | Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis |
| 2023 | Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. | Rui Wang, Pengyu Cheng, Ricardo Henao |
| 2023 | Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group. | Zhenbang Wang, Emanuel Ben-David, Martin Slawski |
| 2023 | Revisiting Weighted Strategy for Non-stationary Parametric Bandits. | Jing Wang, Peng Zhao, Zhi-Hua Zhou |
| 2023 | Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework. | Runzhe Wan, Lin Ge, Rui Song |
| 2023 | Unsupervised representation learning with recognition-parametrised probabilistic models. | William I. Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani |
| 2023 | Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel. | Jonas Wacker, Ruben Ohana, Maurizio Filippone |
| 2023 | Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles. | Rajeev Verma, Daniel Barrejn, Eric T. Nalisnick |
| 2023 | Pointwise sampling uncertainties on the Precision-Recall curve. | Ralph E. Q. Urlus, Max Baak, Stphane Collot, Ilan Fridman Rojas |
| 2023 | Safe Sequential Testing and Effect Estimation in Stratified Count Data. | Rosanne Turner, Peter Grunwald |
| 2023 | Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits. | Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2023 | Deep equilibrium models as estimators for continuous latent variables. | Russell Tsuchida, Cheng Soon Ong |
| 2023 | Multi-Agent congestion cost minimization with linear function approximations. | Prashant Trivedi, Nandyala Hemachandra |
| 2023 | Learning Treatment Effects from Observational and Experimental Data. | Sofia Triantafillou, Fattaneh Jabbari, Gregory F. Cooper |
| 2023 | Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning. | Volodymyr Tkachuk, Seyed Alireza Bakhtiari, Johannes Kirschner, Matej Jusup, Ilija Bogunovic, Csaba Szepesvri |
| 2023 | Gradient-Informed Neural Network Statistical Robustness Estimation. | Karim Tit, Teddy Furon, Mathias Rousset |
| 2023 | On the Complexity of Representation Learning in Contextual Linear Bandits. | Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric |
| 2023 | Rethinking Initialization of the Sinkhorn Algorithm. | James Thornton, Marco Cuturi |
| 2023 | EGG-GAE: scalable graph neural networks for tabular data imputation. | Lev Telyatnikov, Simone Scardapane |
| 2023 | No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities. | Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low |
| 2023 | Manifold Restricted Interventional Shapley Values. | Muhammad Faaiz Taufiq, Patrick Blbaum, Lenon Minorics |