Journal articles on the topic 'Adversarial bandits'
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Lu, Shiyin, Guanghui Wang, and Lijun Zhang. "Stochastic Graphical Bandits with Adversarial Corruptions." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (May 18, 2021): 8749–57. http://dx.doi.org/10.1609/aaai.v35i10.17060.
Full textPacchiano, Aldo, Heinrich Jiang, and Michael I. Jordan. "Robustness Guarantees for Mode Estimation with an Application to Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (May 18, 2021): 9277–84. http://dx.doi.org/10.1609/aaai.v35i10.17119.
Full textWang, Zhiwei, Huazheng Wang, and Hongning Wang. "Stealthy Adversarial Attacks on Stochastic Multi-Armed Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 14 (March 24, 2024): 15770–77. http://dx.doi.org/10.1609/aaai.v38i14.29506.
Full textEsfandiari, Hossein, Amin Karbasi, Abbas Mehrabian, and Vahab Mirrokni. "Regret Bounds for Batched Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 8 (May 18, 2021): 7340–48. http://dx.doi.org/10.1609/aaai.v35i8.16901.
Full textChen, Cheng, Canzhe Zhao, and Shuai Li. "Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (June 28, 2022): 6202–10. http://dx.doi.org/10.1609/aaai.v36i6.20569.
Full textWang, Lingda, Bingcong Li, Huozhi Zhou, Georgios B. Giannakis, Lav R. Varshney, and Zhizhen Zhao. "Adversarial Linear Contextual Bandits with Graph-Structured Side Observations." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 11 (May 18, 2021): 10156–64. http://dx.doi.org/10.1609/aaai.v35i11.17218.
Full textWachel, Pawel, and Cristian Rojas. "An Adversarial Approach to Adaptive Model Predictive Control." Journal of Advances in Applied & Computational Mathematics 9 (September 19, 2022): 135–46. http://dx.doi.org/10.15377/2409-5761.2022.09.10.
Full textXu, Xiao, and Qing Zhao. "Memory-Constrained No-Regret Learning in Adversarial Multi-Armed Bandits." IEEE Transactions on Signal Processing 69 (2021): 2371–82. http://dx.doi.org/10.1109/tsp.2021.3070201.
Full textShi, Chengshuai, and Cong Shen. "On No-Sensing Adversarial Multi-Player Multi-Armed Bandits With Collision Communications." IEEE Journal on Selected Areas in Information Theory 2, no. 2 (June 2021): 515–33. http://dx.doi.org/10.1109/jsait.2021.3076027.
Full textTae, Ki Hyun, Hantian Zhang, Jaeyoung Park, Kexin Rong, and Steven Euijong Whang. "Falcon: Fair Active Learning Using Multi-Armed Bandits." Proceedings of the VLDB Endowment 17, no. 5 (January 2024): 952–65. http://dx.doi.org/10.14778/3641204.3641207.
Full textCheung, Wang Chi, David Simchi-Levi, and Ruihao Zhu. "Hedging the Drift: Learning to Optimize Under Nonstationarity." Management Science 68, no. 3 (March 2022): 1696–713. http://dx.doi.org/10.1287/mnsc.2021.4024.
Full textGuan, Ziwei, Kaiyi Ji, Donald J. Bucci Jr., Timothy Y. Hu, Joseph Palombo, Michael Liston, and Yingbin Liang. "Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4036–43. http://dx.doi.org/10.1609/aaai.v34i04.5821.
Full textLattimore, Tor. "Improved regret for zeroth-order adversarial bandit convex optimisation." Mathematical Statistics and Learning 2, no. 3 (October 16, 2020): 311–34. http://dx.doi.org/10.4171/msl/17.
Full textZhao, Haihong, Xinbin Li, Song Han, Lei Yan, and Xinping Guan. "Adaptive OFDM underwater acoustic transmission: An adversarial bandit approach." Neurocomputing 385 (April 2020): 148–59. http://dx.doi.org/10.1016/j.neucom.2019.12.063.
Full textEsfandiari, Hossein, MohammadTaghi HajiAghayi, Brendan Lucier, and Michael Mitzenmacher. "Online Pandora’s Boxes and Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1885–92. http://dx.doi.org/10.1609/aaai.v33i01.33011885.
Full textVural, Nuri Mert, Hakan Gokcesu, Kaan Gokcesu, and Suleyman S. Kozat. "Minimax Optimal Algorithms for Adversarial Bandit Problem With Multiple Plays." IEEE Transactions on Signal Processing 67, no. 16 (August 15, 2019): 4383–98. http://dx.doi.org/10.1109/tsp.2019.2928952.
Full textGokcesu, Kaan, and Suleyman Serdar Kozat. "An Online Minimax Optimal Algorithm for Adversarial Multiarmed Bandit Problem." IEEE Transactions on Neural Networks and Learning Systems 29, no. 11 (November 2018): 5565–80. http://dx.doi.org/10.1109/tnnls.2018.2806006.
Full textWang, Siwei, Haoyun Wang, and Longbo Huang. "Adaptive Algorithms for Multi-armed Bandit with Composite and Anonymous Feedback." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 11 (May 18, 2021): 10210–17. http://dx.doi.org/10.1609/aaai.v35i11.17224.
Full textBychkov, G. K., D. M. Dvinskikh, A. V. Antsiferova, A. V. Gasnikov, and A. V. Lobanov. "Accelerated Zero-Order SGD under High-Order Smoothness and Overparameterized Regime." Nelineinaya Dinamika 20, no. 5 (2024): 759–88. https://doi.org/10.20537/nd241209.
Full textAvadhanula, Vashist, Andrea Celli, Riccardo Colini-Baldeschi, Stefano Leonardi, and Matteo Russo. "Fully Dynamic Online Selection through Online Contention Resolution Schemes." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 6 (June 26, 2023): 6693–700. http://dx.doi.org/10.1609/aaai.v37i6.25821.
Full textDai, Yan, and Longbo Huang. "Adversarial Network Optimization under Bandit Feedback: Maximizing Utility in Non-Stationary Multi-Hop Networks." Proceedings of the ACM on Measurement and Analysis of Computing Systems 8, no. 3 (December 10, 2024): 1–48. https://doi.org/10.1145/3700413.
Full textBao, Hongyan, Yufei Han, Yujun Zhou, Xin Gao, and Xiangliang Zhang. "Towards Efficient and Domain-Agnostic Evasion Attack with High-Dimensional Categorical Inputs." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 6 (June 26, 2023): 6753–61. http://dx.doi.org/10.1609/aaai.v37i6.25828.
Full textYang, Jianyi, and Shaolei Ren. "Robust Bandit Learning with Imperfect Context." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (May 18, 2021): 10594–602. http://dx.doi.org/10.1609/aaai.v35i12.17267.
Full textRamanujan, Raghuram, Ashish Sabharwal, and Bart Selman. "On Adversarial Search Spaces and Sampling-Based Planning." Proceedings of the International Conference on Automated Planning and Scheduling 20 (May 25, 2021): 242–45. http://dx.doi.org/10.1609/icaps.v20i1.13437.
Full textLancewicki, Tal, Aviv Rosenberg, and Yishay Mansour. "Learning Adversarial Markov Decision Processes with Delayed Feedback." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 7 (June 28, 2022): 7281–89. http://dx.doi.org/10.1609/aaai.v36i7.20690.
Full textWang, Peng, Jingju Liu, Dongdong Hou, and Shicheng Zhou. "A Cybersecurity Knowledge Graph Completion Method Based on Ensemble Learning and Adversarial Training." Applied Sciences 12, no. 24 (December 16, 2022): 12947. http://dx.doi.org/10.3390/app122412947.
Full textXu, Jianyu, Bin Liu, Huadong Mo, and Daoyi Dong. "Bayesian adversarial multi-node bandit for optimal smart grid protection against cyber attacks." Automatica 128 (June 2021): 109551. http://dx.doi.org/10.1016/j.automatica.2021.109551.
Full textHyeong Soo Chang, Jiaqiao Hu, M. C. Fu, and S. I. Marcus. "Adaptive Adversarial Multi-Armed Bandit Approach to Two-Person Zero-Sum Markov Games." IEEE Transactions on Automatic Control 55, no. 2 (February 2010): 463–68. http://dx.doi.org/10.1109/tac.2009.2036333.
Full textKillian, Jackson A., Arpita Biswas, Lily Xu, Shresth Verma, Vineet Nair, Aparna Taneja, Aparna Hegde, et al. "Robust Planning over Restless Groups: Engagement Interventions for a Large-Scale Maternal Telehealth Program." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (June 26, 2023): 14295–303. http://dx.doi.org/10.1609/aaai.v37i12.26672.
Full textBubeck, Sébastien, Ronen Eldan, and Yin Tat Lee. "Kernel-based Methods for Bandit Convex Optimization." Journal of the ACM 68, no. 4 (June 30, 2021): 1–35. http://dx.doi.org/10.1145/3453721.
Full textSudianto, Edi. "Digest: Banding together to battle adversaries has its consequences*." Evolution 73, no. 6 (April 24, 2019): 1320–21. http://dx.doi.org/10.1111/evo.13750.
Full textDoan, Thang, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, and R. Devon Hjelm. "On-Line Adaptative Curriculum Learning for GANs." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3470–77. http://dx.doi.org/10.1609/aaai.v33i01.33013470.
Full textAmballa, Chaitanya, Manu K. Gupta, and Sanjay P. Bhat. "Computing an Efficient Exploration Basis for Learning with Univariate Polynomial Features." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 8 (May 18, 2021): 6636–43. http://dx.doi.org/10.1609/aaai.v35i8.16821.
Full textHan, Song, Xinbin Li, Lei Yan, Jiajie Xu, Zhixin Liu, and Xinping Guan. "Joint resource allocation in underwater acoustic communication networks: A game-based hierarchical adversarial multiplayer multiarmed bandit algorithm." Information Sciences 454-455 (July 2018): 382–400. http://dx.doi.org/10.1016/j.ins.2018.05.011.
Full textRichie, Rodney C. "Basics of Artificial Intelligence (AI) Modeling." Journal of Insurance Medicine 51, no. 1 (May 28, 2024): 35–40. http://dx.doi.org/10.17849/insm-51-1-35-40.1.
Full textFarina, Gabriele, Robin Schmucker, and Tuomas Sandholm. "Bandit Linear Optimization for Sequential Decision Making and Extensive-Form Games." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 6 (May 18, 2021): 5372–80. http://dx.doi.org/10.1609/aaai.v35i6.16677.
Full textKamikokuryo, Kenta, Takumi Haga, Gentiane Venture, and Vincent Hernandez. "Adversarial Autoencoder and Multi-Armed Bandit for Dynamic Difficulty Adjustment in Immersive Virtual Reality for Rehabilitation: Application to Hand Movement." Sensors 22, no. 12 (June 14, 2022): 4499. http://dx.doi.org/10.3390/s22124499.
Full textMéndez Lara, Francisco Iván. "Francisco Villa en la prensa carrancista (1914-1915). La construcción del adversario." Bibliographica 3, no. 1 (March 6, 2020): 211. http://dx.doi.org/10.22201/iib.2594178xe.2020.1.56.
Full textRiou, Matthieu, Bassam Jabaian, Stéphane Huet, and Fabrice Lefèvre. "Reinforcement adaptation of an attention-based neural natural language generator for spoken dialogue systems." Dialogue & Discourse 10, no. 1 (February 22, 2019): 1–19. http://dx.doi.org/10.5087/dad.2019.101.
Full textVu, Dong Quan, Patrick Loiseau, Alonso Silva, and Long Tran-Thanh. "Path Planning Problems with Side Observations—When Colonels Play Hide-and-Seek." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 2252–59. http://dx.doi.org/10.1609/aaai.v34i02.5602.
Full textHe, Jianhao, Feidiao Yang, Jialin Zhang, and Lvzhou Li. "Quantum algorithm for online convex optimization." Quantum Science and Technology 7, no. 2 (March 17, 2022): 025022. http://dx.doi.org/10.1088/2058-9565/ac5919.
Full textEckardt, Jan-Niklas, Waldemar Hahn, Christoph Röllig, Sebastian Stasik, Uwe Platzbecker, Carsten Müller-Tidow, Hubert Serve, et al. "Mimicking Clinical Trials with Synthetic Acute Myeloid Leukemia Patients Using Generative Artificial Intelligence." Blood 142, Supplement 1 (November 28, 2023): 2268. http://dx.doi.org/10.1182/blood-2023-179817.
Full textImmorlica, Nicole, Karthik Abinav Sankararaman, Robert Schapire, and Aleksandrs Slivkins. "Adversarial Bandits with Knapsacks." Journal of the ACM, August 18, 2022. http://dx.doi.org/10.1145/3557045.
Full textDong, Yanyan, and Vincent Y. F. Tan. "Adversarial Combinatorial Bandits with Switching Costs." IEEE Transactions on Information Theory, 2024, 1. http://dx.doi.org/10.1109/tit.2024.3384033.
Full textLykouris, Thodoris, Karthik Sridharan, and Éva Tardos. "Small-Loss Bounds for Online Learning with Partial Information." Mathematics of Operations Research, January 25, 2022. http://dx.doi.org/10.1287/moor.2021.1204.
Full textAlipour-Fanid, Amir, Monireh Dabaghchian, and Kai Zeng. "Self-Unaware Adversarial Multi-Armed Bandits With Switching Costs." IEEE Transactions on Neural Networks and Learning Systems, 2021, 1–15. http://dx.doi.org/10.1109/tnnls.2021.3110194.
Full textZhou, Datong, and Claire Tomlin. "Budget-Constrained Multi-Armed Bandits With Multiple Plays." Proceedings of the AAAI Conference on Artificial Intelligence 32, no. 1 (April 29, 2018). http://dx.doi.org/10.1609/aaai.v32i1.11629.
Full textLi, Yandi, Jianxiong Guo, Yupeng Li, Tian Wang, and Weijia Jia. "Adversarial Bandits With Multi-User Delayed Feedback: Theory and Application." IEEE Transactions on Mobile Computing, 2024, 1–15. http://dx.doi.org/10.1109/tmc.2024.3362237.
Full textTossou, Aristide, and Christos Dimitrakakis. "Achieving Privacy in the Adversarial Multi-Armed Bandit." Proceedings of the AAAI Conference on Artificial Intelligence 31, no. 1 (February 13, 2017). http://dx.doi.org/10.1609/aaai.v31i1.10896.
Full textHuang, Yin, Lei Wang, and Jie Xu. "Quantum Entanglement Path Selection and Qubit Allocation via Adversarial Group Neural Bandits." IEEE/ACM Transactions on Networking, 2024, 1–12. https://doi.org/10.1109/tnet.2024.3510550.
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