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Enhancing robustness of machine learning systems via data transformations.

A. Bhagoji, D. Cullina, C. Sitawarin, and P. Mittal. CISS, page 1-5. IEEE, (2018)

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Analyzing the Robustness of Open-World Machine Learning.V. Sehwag, A. Bhagoji, L. Song, C. Sitawarin, D. Cullina, M. Chiang, and P. Mittal. AISec@CCS, page 105-116. ACM, (2019)Enhancing robustness of machine learning systems via data transformations.A. Bhagoji, D. Cullina, C. Sitawarin, and P. Mittal. CISS, page 1-5. IEEE, (2018)REAP: A Large-Scale Realistic Adversarial Patch Benchmark.N. Hingun, C. Sitawarin, J. Li, and D. Wagner. ICCV, page 4617-4628. IEEE, (2023)OODRobustBench: benchmarking and analyzing adversarial robustness under distribution shift.L. Li, Y. Wang, C. Sitawarin, and M. Spratling. CoRR, (2023)Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems.C. Sitawarin, F. Tramèr, and N. Carlini. ICML, volume 202 of Proceedings of Machine Learning Research, page 32008-32032. PMLR, (2023)Improving Adversarial Robustness Through Progressive Hardening.C. Sitawarin, S. Chakraborty, and D. Wagner. CoRR, (2020)Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos.C. Sitawarin, A. Bhagoji, A. Mosenia, P. Mittal, and M. Chiang. CoRR, (2018)Minimum-Norm Adversarial Examples on KNN and KNN based Models.C. Sitawarin, and D. Wagner. SP (Workshops), page 34-40. IEEE, (2020)Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams.C. Sitawarin, E. Kornaropoulos, D. Song, and D. Wagner. NeurIPS, page 15486-15497. (2021)DARTS: Deceiving Autonomous Cars with Toxic Signs.C. Sitawarin, A. Bhagoji, A. Mosenia, M. Chiang, and P. Mittal. CoRR, (2018)

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Disambiguation of "Sitawarin, Chawin"

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Enhancing robustness of machine learning systems via data transformations.

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Disambiguation of "Sitawarin, Chawin"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Enhancing robustness of machine learning systems via data transformations.

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Enhancing robustness of machine learning systems via data transformations.