| 2022 | Near optimal efficient decoding from pooled data. | Max Hahn-Klimroth, Nola Mller |
| 2022 | Faster online calibration without randomization: interval forecasts and the power of two choices. | Chirag Gupta, Aaditya Ramdas |
| 2022 | Sharp Constants in Uniformity Testing via the Huber Statistic. | Shivam Gupta, Eric Price |
| 2022 | Online Learning to Transport via the Minimal Selection Principle. | Wenxuan Guo, YoonHaeng Hur, Tengyuan Liang, Chris Ryan |
| 2022 | Hardness of Maximum Likelihood Learning of DPPs. | Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie |
| 2022 | Private Convex Optimization via Exponential Mechanism. | Sivakanth Gopi, Yin Tat Lee, Daogao Liu |
| 2022 | Low-Degree Multicalibration. | Parikshit Gopalan, Michael P. Kim, Mihir Singhal, Shengjia Zhao |
| 2022 | Can Q-learning be Improved with Advice? | Noah Golowich, Ankur Moitra |
| 2022 | Exact Community Recovery in Correlated Stochastic Block Models. | Julia Gaudio, Mikls Z. Rcz, Anirudh Sridhar |
| 2022 | New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees. | Dan Garber, Ben Kretzu |
| 2022 | Approximate Cluster Recovery from Noisy Labels. | Buddhima Gamlath, Silvio Lattanzi, Ashkan Norouzi-Fard, Ola Svensson |
| 2022 | Efficient decentralized multi-agent learning in asymmetric queuing systems. | Daniel Freund, Thodoris Lykouris, Wentao Weng |
| 2022 | Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data. | Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett |
| 2022 | Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation. | Dylan J. Foster, Akshay Krishnamurthy, David Simchi-Levi, Yunzong Xu |
| 2022 | The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance. | Matthew Faw, Isidoros Tziotis, Constantine Caramanis, Aryan Mokhtari, Sanjay Shakkottai, Rachel A. Ward |
| 2022 | How catastrophic can catastrophic forgetting be in linear regression? | Itay Evron, Edward Moroshko, Rachel A. Ward, Nathan Srebro, Daniel Soudry |
| 2022 | Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information. | Yonathan Efroni, Dylan J. Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford |
| 2022 | Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators. | Carles Domingo-Enrich |
| 2022 | Fast algorithm for overcomplete order-3 tensor decomposition. | Jingqiu Ding, Tommaso d'Orsi, Chih-Hung Liu, David Steurer, Stefan Tiegel |
| 2022 | Learning a Single Neuron with Adversarial Label Noise via Gradient Descent. | Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis |
| 2022 | Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models. | Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun |
| 2022 | Robust Sparse Mean Estimation via Sum of Squares. | Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas |
| 2022 | Non-Gaussian Component Analysis via Lattice Basis Reduction. | Ilias Diakonikolas, Daniel Kane |
| 2022 | Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise. | Ilias Diakonikolas, Daniel Kane |
| 2022 | Neural Networks can Learn Representations with Gradient Descent. | Alexandru Damian, Jason D. Lee, Mahdi Soltanolkotabi |