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Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin

, and . (2019)cite arxiv:1910.04284.

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Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin, and . (2019)cite arxiv:1910.04284.Safe Reinforcement Learning by Imagining the Near Future, , and . (2022)cite arxiv:2202.07789Comment: Accepted at NeurIPS 2021.In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness., , , , , and . CoRR, (2020)Self-training Avoids Using Spurious Features Under Domain Shift., , , and . NeurIPS, (2020)Fine-Grained Gap-Dependent Bounds for Tabular MDPs via Adaptive Multi-Step Bootstrap., , and . COLT, volume 134 of Proceedings of Machine Learning Research, page 4438-4472. PMLR, (2021)In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness., , , , , and . ICLR, OpenReview.net, (2021)Optimal Regularization can Mitigate Double Descent., , , and . ICLR, OpenReview.net, (2021)Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 17221-17237. PMLR, (2022)Robust and On-the-Fly Dataset Denoising for Image Classification., , , and . ECCV (29), volume 12374 of Lecture Notes in Computer Science, page 556-572. Springer, (2020)A Simple but Tough-to-Beat Baseline for Sentence Embeddings., , and . ICLR (Poster), OpenReview.net, (2017)