WebFeb 10, 2024 · Adversarial Attacks on Linear Contextual Bandits. Contextual bandit algorithms are applied in a wide range of domains, from advertising to recommender systems, from clinical trials to education. In many of these domains, malicious agents may have incentives to attack the bandit algorithm to induce it to perform a desired behavior. WebY. Ma, K.-S. Jun, L. Li, and J. Zhu: Data poisoning attacks in contextual bandits. In the 9th Conference on Decision and Game Theory for Security (GameSec), ... L. Li, W. Chu, J. Langford, and R.E. Schapire: A contextual-bandit approach to personalized news article recommendation. In the 19th International Conference on World Wide Web ...
Data Poisoning Attacks in Contextual Bandits - arXiv
WebAug 17, 2024 · We study offline data poisoning attacks in contextual bandits, a class of reinforcement learning problems with important applications in online recommendation … WebMay 16, 2024 · Stochastic multi-armed bandits form a class of online learning problems that have important applications in online recommendation systems, adaptive medical treatment, and many others. Even though potential attacks against these learning algorithms may hijack their behavior, causing catastrophic loss in real-world applications, little is known ... inc5000 log in
Dataset Security for Machine Learning: Data Poisoning, …
WebSep 26, 2024 · Data Poisoning Attacks in Contextual Bandits: 9th International Conference, GameSec 2024, Seattle, WA, USA, October 29–31, 2024, Proceedings … WebSep 26, 2024 · Data Poisoning Attacks in Contextual Bandits: 9th International Conference, GameSec 2024, Seattle, WA, USA, October 29–31, 2024, Proceedings September 2024 DOI: 10.1007/978-3-030-01554-1_11 WebSyndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms QIN DING, Yue Kang, Yi-Wei Liu, Thomas Chun Man Lee, Cho-Jui Hsieh, James Sharpnack; ... A Powerful Defense against Data Poisoning Attack Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman; inc5937076