| 2022 | Dynamic relocation in ridesharing via fixpoint construction. | Ian A. Kash, Zhongkai Wen, Lenore D. Zuck |
| 2022 | Improved feature importance computation for tree models based on the Banzhaf value. | Adam Karczmarz, Tomasz P. Michalak, Anish Mukherjee, Piotr Sankowski, Piotr Wygocki |
| 2022 | Test for non-negligible adverse shifts. | Vathy M. Kamulete |
| 2022 | Optimal control of partially observable Markov decision processes with finite linear temporal logic constraints. | Krishna Chaitanya Kalagarla, Dhruva Kartik, Dongming Shen, Rahul Jain, Ashutosh Nayyar, Pierluigi Nuzzo |
| 2022 | Decision-theoretic planning with communication in open multiagent systems. | Anirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh |
| 2022 | If you've trained one you've trained them all: inter-architecture similarity increases with robustness. | Haydn Thomas Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore |
| 2022 | Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound. | Hongwei Jin, Zishun Yu, Xinhua Zhang |
| 2022 | Fedvarp: Tackling the variance due to partial client participation in federated learning. | Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi |
| 2022 | Towards painless policy optimization for constrained MDPs. | Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesvari, Doina Precup |
| 2022 | Balancing utility and scalability in metric differential privacy. | Jacob Imola, Shiva Prasad Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier |
| 2022 | Binary independent component analysis: a non-stationarity-based approach. | Antti Hyttinen, Vitria Barin Pacela, Aapo Hyvrinen |
| 2022 | Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison. | Eyke Hllermeier, Sbastien Destercke, Mohammad Hossein Shaker |
| 2022 | Uncertainty-aware pseudo-labeling for quantum calculations. | Kexin Huang, Vishnu Sresht, Brajesh K. Rai, Mykola Bordyuh |
| 2022 | Near-optimal Thompson sampling-based algorithms for differentially private stochastic bandits. | Bingshan Hu, Nidhi Hegde |
| 2022 | CIGMO: Categorical invariant representations in a deep generative framework. | Haruo Hosoya |
| 2022 | Fast predictive uncertainty for classification with Bayesian deep networks. | Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig |
| 2022 | Quadratic metric elicitation for fairness and beyond. | Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo |
| 2022 | Learning sparse representations of preferences within Choquet expected utility theory. | Margot Herin, Patrice Perny, Nataliya Sokolovska |
| 2022 | Variational multiple shooting for Bayesian ODEs with Gaussian processes. | Pashupati Hegde, agatay Yildiz, Harri Lhdesmki, Samuel Kaski, Markus Heinonen |
| 2022 | Reinforcement learning in many-agent settings under partial observability. | Keyang He, Prashant Doshi, Bikramjit Banerjee |
| 2022 | Generalizing off-policy learning under sample selection bias. | Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel |
| 2022 | Modeling extremes with d-max-decreasing neural networks. | Ali Hasan, Khalil Elkhalil, Yuting Ng, Joo M. Pereira, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh |
| 2022 | Learning a neural Pareto manifold extractor with constraints. | Soumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, Matthew Lease |
| 2022 | Efficient and transferable adversarial examples from bayesian neural networks. | Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen |
| 2022 | Robust expected information gain for optimal Bayesian experimental design using ambiguity sets. | Jinwoo Go, Tobin Isaac |