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A \FRAMEWORK\ \FOR\ \ROBUSTNESS\ \CERTIFICATION\ ØF\ \SMOOTHED\ \CLASSIFIERS\ \USING\ F-\DIVERGENCES\, , , , , , , , and . International Conference on Learning Representations, (2020)Adversarially Robust Representations with Smooth Encoders, , , and . International Conference on Learning Representations, (2020)Adversarially Robust Representations with Smooth Encoders., , , and . ICLR, OpenReview.net, (2020)Provably Correct Physics-Informed Neural Networks., , , , , and . CoRR, (2023)Stealing Part of a Production Language Model., , , , , , , , , and 3 other author(s). CoRR, (2024)Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control., , , , , , and . ICLR, OpenReview.net, (2020)(Certified!!) Adversarial Robustness for Free!, , , , , and . ICLR, OpenReview.net, (2023)Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play., , , , , , and . CoRR, (2023)Efficient Neural Network Verification with Exactness Characterization., , , , , and . UAI, volume 115 of Proceedings of Machine Learning Research, page 497-507. AUAI Press, (2019)The NodeHopper: Enabling Low Latency Ranking with Constraints via a Fast Dual Solver., , , , , , and . KDD, page 1285-1294. ACM, (2020)