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ASPEST: Bridging the Gap Between Active Learning and Selective Prediction.

, , , , , и . Trans. Mach. Learn. Res., (2024)

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Jiefeng Chen

Jiefeng Cheng

Chen Chen

Chen Chen

Shih Chen Chen

 

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Concise Explanations of Neural Networks using Adversarial Training., , , , и . CoRR, (2018)ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining., , , , и . ECML/PKDD (3), том 12977 из Lecture Notes in Computer Science, стр. 430-445. Springer, (2021)Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks., , , , и . EuroS&P, стр. 480-495. IEEE, (2019)Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual Classification., , , , , и . CoRR, (2020)Is Forgetting Less a Good Inductive Bias for Forward Transfer?, , , и . ICLR, OpenReview.net, (2023)Concept-based Explanations for Out-of-Distribution Detectors., , , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 5817-5837. PMLR, (2023)Towards Evaluating the Robustness of Neural Networks Learned by Transduction., , , , и . ICLR, OpenReview.net, (2022)Stratified Adversarial Robustness with Rejection., , , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 4867-4894. PMLR, (2023)GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems., , , , , и . EuroS&P, стр. 664-683. IEEE, (2022)Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation., , , , , и . CoRR, (2020)