{"type":"ScholarlyArticle","title":"Adversarial Machine Learning with Double Oracle","authors":[{"name":"Kai Wang","slug":"kai-wang","given":"Kai","family":"Wang","affiliation":"Department of Computer Science , University of Southern California , USA"}],"abstract":"We aim to improve the general adversarial machine learning solution by introducing the double oracle idea from game theory, which is commonly used to solve a sequential zero-sum game, where the adversarial machine learning problem can be formulated as a zero-sum minimax problem between learner and attacker.","doi":"10.24963/ijcai.2019/925","url":"https://ijcai.org/proceedings/2019/925","pdf":"https://ijcai.org/proceedings/2019/0925.pdf","markdown":"https://ijcai.org/proceedings/2019/925.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/925","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":925,"pages":{"first":6472,"last":6473},"keywords":["Machine Learning: Adversarial Machine Learning","Agent-based and Multi-agent Systems: Algorithmic Game Theory","Machine Learning: Ensemble Methods"],"videos":[],"references":[{"position":1,"raw":"[Athalye et al., 2018] Anish Athalye, Nicholas Carlini, and David Wagner. Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples. ICML, 2018.","title":"Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples","authors":"Anish Athalye, Nicholas Carlini, David Wagner","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Goodfellow et al., 2014] Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy. Explaining and harnessing adversarial examples. CoRR, 2014.","title":"Explaining and harnessing adversarial examples","authors":"Ian J Goodfellow, Jonathon Shlens, Christian Szegedy","year":"2014","venue":null,"doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Jain et al., 2011] Manish Jain, Dmytro Korzhyk, Ondřej Vaněk, Vincent Conitzer, Michal Pěchouček, and Milind Tambe. A double oracle algorithm for zero-sum security games on graphs. AAMAS, 2011.","title":"A double oracle algorithm for zero-sum security games on graphs","authors":"Manish Jain, Dmytro Korzhyk, Ondřej Vaněk, Vincent Conitzer, Michal Pěchouček, Milind Tambe","year":"2011","venue":"AAMAS","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Madry et al., 2017] Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. Towards deep learning models resistant to adversarial attacks. ICLR, 2017.","title":"Towards deep learning models resistant to adversarial attacks","authors":"Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu","year":"2017","venue":"ICLR","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[McMahan et al., 2003] H Brendan McMahan, Geoffrey J Gordon, and Avrim Blum. Planning in the presence of cost functions controlled by an adversary. ICML, 2003.","title":"Planning in the presence of cost functions controlled by an adversary","authors":"Geoffrey J H Brendan Mcmahan, Avrim Gordon, Blum","year":"2003","venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}