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Fair Robust Active Learning by Joint Inconsistency., , , и . ICCV (Workshops), стр. 3624-3633. IEEE, (2023)Diversified Strategies for Mitigating Adversarial Attacks in Multiagent Systems., , и . AAMAS, стр. 407-415. International Foundation for Autonomous Agents and Multiagent Systems Richland, SC, USA / ACM, (2018)Boosting with Online Binary Learners for the Multiclass Bandit Problem., , и . ICML, том 32 из JMLR Workshop and Conference Proceedings, стр. 342-350. JMLR.org, (2014)Benchmarking renderscript: potential for energy efficient multi-core mobile devices., , и . SECON Workshops, стр. 25-30. IEEE, (2015)Fair Robust Active Learning by Joint Inconsistency., , и . CoRR, (2022)Robust Physical Adversarial Attack on Faster R-CNN Object Detector., , , и . CoRR, (2018)An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes., , , , , , , , , и 5 other автор(ы). KDD Cup, том 7 из JMLR Proceedings, стр. 57-64. JMLR.org, (2009)AI-infused Security: Robust Defense by Bridging Theory and Practice.. Georgia Institute of Technology, Atlanta, GA, USA, (2020)base-search.net (ftgeorgiatech:oai:smartech.gatech.edu:1853/62296).Exploratory Visual Analytics of Mobile Health Data: Sensemaking Challenges and Opportunities., , , , , и . Mobile Health - Sensors, Analytic Methods, and Applications, Springer, (2017)Communication Efficient Distributed Agnostic Boosting., , и . AISTATS, том 51 из JMLR Workshop and Conference Proceedings, стр. 1299-1307. JMLR.org, (2016)