| 2022 | Loss as the Inconsistency of a Probabilistic Dependency Graph: Choose Your Model, Not Your Loss Function. | Oliver E. Richardson |
| 2022 | Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference. | Luca Rendsburg, Agustinus Kristiadi, Philipp Hennig, Ulrike von Luxburg |
| 2022 | Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. | Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho |
| 2022 | Optimizing Early Warning Classifiers to Control False Alarms via a Minimum Precision Constraint. | Preetish Rath, Michael C. Hughes |
| 2022 | Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization. | Marco Rando, Luigi Carratino, Silvia Villa, Lorenzo Rosasco |
| 2022 | Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers. | Alain Rakotomamonjy, Rmi Flamary, Joseph Salmon, Gilles Gasso |
| 2022 | Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD Learning. | Anant Raj, Pooria Joulani, Andrs Gyrgy, Csaba Szepesvri |
| 2022 | Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning. | Xun Qian, Rustem Islamov, Mher Safaryan, Peter Richtrik |
| 2022 | Almost Optimal Universal Lower Bound for Learning Causal DAGs with Atomic Interventions. | Vibhor Porwal, Piyush Srivastava, Gaurav Sinha |
| 2022 | Contrasting the landscape of contrastive and non-contrastive learning. | Ashwini Pokle, Jinjin Tian, Yuchen Li, Andrej Risteski |
| 2022 | Feature screening with kernel knockoffs. | Benjamin Poignard, Peter J. Naylor, Hctor Climente-Gonzlez, Makoto Yamada |
| 2022 | Metalearning Linear Bandits by Prior Update. | Amit Peleg, Naama Pearl, Ron Meir |
| 2022 | Hypergraph Simultaneous Generators. | Bahman Pedrood, Carlotta Domeniconi, Kathryn B. Laskey |
| 2022 | Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis. | Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju |
| 2022 | Quadric Hypersurface Intersection for Manifold Learning in Feature Space. | Fedor Pavutnitskiy, Sergei O. Ivanov, Evgeniy Abramov, Viacheslav Borovitskiy, Artem Klochkov, Viktor Vyalov, Anatolii Zaikovskii, Aleksandr Petiushko |
| 2022 | Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional Consistency. | Eduardo Pavez |
| 2022 | Estimating Functionals of the Out-of-Sample Error Distribution in High-Dimensional Ridge Regression. | Pratik Patil, Alessandro Rinaldo, Ryan J. Tibshirani |
| 2022 | Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. | Youngsuk Park, Danielle C. Maddix, Franois-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang |
| 2022 | Permutation Equivariant Layers for Higher Order Interactions. | Horace Pan, Risi Kondor |
| 2022 | SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification. | Ashwinee Panda, Saeed Mahloujifar, Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal |
| 2022 | Sample Complexity of Robust Reinforcement Learning with a Generative Model. | Kishan Panaganti, Dileep M. Kalathil |
| 2022 | On Learning Mixture Models with Sparse Parameters. | Soumyabrata Pal, Arya Mazumdar |
| 2022 | PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency. | Arun Padakandla, Abram Magner |
| 2022 | Vanishing Curvature in Randomly Initialized Deep ReLU Networks. | Antonio Orvieto, Jonas Kohler, Dario Pavllo, Thomas Hofmann, Aurlien Lucchi |
| 2022 | Diversity and Generalization in Neural Network Ensembles. | Luis A. Ortega, Rafael Cabaas, Andrs R. Masegosa |