Статті в журналах з теми "Stochastic Multi-armed Bandit"
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Xiong, Guojun, and Jian Li. "Decentralized Stochastic Multi-Player Multi-Armed Walking Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 9 (June 26, 2023): 10528–36. http://dx.doi.org/10.1609/aaai.v37i9.26251.
Повний текст джерелаCiucanu, Radu, Pascal Lafourcade, Gael Marcadet, and Marta Soare. "SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits." Journal of Artificial Intelligence Research 73 (February 23, 2022): 737–65. http://dx.doi.org/10.1613/jair.1.13163.
Повний текст джерелаWan, Zongqi, Zhijie Zhang, Tongyang Li, Jialin Zhang, and Xiaoming Sun. "Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 8 (June 26, 2023): 10087–94. http://dx.doi.org/10.1609/aaai.v37i8.26202.
Повний текст джерелаLesage-Landry, Antoine, and Joshua A. Taylor. "The Multi-Armed Bandit With Stochastic Plays." IEEE Transactions on Automatic Control 63, no. 7 (July 2018): 2280–86. http://dx.doi.org/10.1109/tac.2017.2765501.
Повний текст джерелаEsfandiari, 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.
Повний текст джерелаDzhoha, A. S. "Sequential resource allocation in a stochastic environment: an overview and numerical experiments." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 3 (2021): 13–25. http://dx.doi.org/10.17721/1812-5409.2021/3.1.
Повний текст джерелаJuditsky, A., A. V. Nazin, A. B. Tsybakov, and N. Vayatis. "Gap-free Bounds for Stochastic Multi-Armed Bandit." IFAC Proceedings Volumes 41, no. 2 (2008): 11560–63. http://dx.doi.org/10.3182/20080706-5-kr-1001.01959.
Повний текст джерелаAllesiardo, Robin, Raphaël Féraud, and Odalric-Ambrym Maillard. "The non-stationary stochastic multi-armed bandit problem." International Journal of Data Science and Analytics 3, no. 4 (March 30, 2017): 267–83. http://dx.doi.org/10.1007/s41060-017-0050-5.
Повний текст джерелаHuo, Xiaoguang, and Feng Fu. "Risk-aware multi-armed bandit problem with application to portfolio selection." Royal Society Open Science 4, no. 11 (November 2017): 171377. http://dx.doi.org/10.1098/rsos.171377.
Повний текст джерелаXu, Lily, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, and Milind Tambe. "Dual-Mandate Patrols: Multi-Armed Bandits for Green Security." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 14974–82. http://dx.doi.org/10.1609/aaai.v35i17.17757.
Повний текст джерелаPatil, Vishakha, Ganesh Ghalme, Vineet Nair, and Y. Narahari. "Achieving Fairness in the Stochastic Multi-Armed Bandit Problem." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 5379–86. http://dx.doi.org/10.1609/aaai.v34i04.5986.
Повний текст джерелаJain, Shweta, Satyanath Bhat, Ganesh Ghalme, Divya Padmanabhan, and Y. Narahari. "Mechanisms with learning for stochastic multi-armed bandit problems." Indian Journal of Pure and Applied Mathematics 47, no. 2 (June 2016): 229–72. http://dx.doi.org/10.1007/s13226-016-0186-3.
Повний текст джерелаCowan, Wesley, and Michael N. Katehakis. "MULTI-ARMED BANDITS UNDER GENERAL DEPRECIATION AND COMMITMENT." Probability in the Engineering and Informational Sciences 29, no. 1 (October 10, 2014): 51–76. http://dx.doi.org/10.1017/s0269964814000217.
Повний текст джерелаDunn, R. T., and K. D. Glazebrook. "The performance of index-based policies for bandit problems with stochastic machine availability." Advances in Applied Probability 33, no. 2 (June 2001): 365–90. http://dx.doi.org/10.1017/s0001867800010843.
Повний текст джерелаBubeck, Sébastien. "Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems." Foundations and Trends® in Machine Learning 5, no. 1 (2012): 1–122. http://dx.doi.org/10.1561/2200000024.
Повний текст джерелаZayas-Cabán, Gabriel, Stefanus Jasin, and Guihua Wang. "An asymptotically optimal heuristic for general nonstationary finite-horizon restless multi-armed, multi-action bandits." Advances in Applied Probability 51, no. 03 (September 2019): 745–72. http://dx.doi.org/10.1017/apr.2019.29.
Повний текст джерелаRoy Chaudhuri, Arghya, and Shivaram Kalyanakrishnan. "Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 06 (April 3, 2020): 10085–92. http://dx.doi.org/10.1609/aaai.v34i06.6566.
Повний текст джерелаO'Flaherty, Brendan. "Some results on two-armed bandits when both projects vary." Journal of Applied Probability 26, no. 3 (September 1989): 655–58. http://dx.doi.org/10.2307/3214424.
Повний текст джерелаO'Flaherty, Brendan. "Some results on two-armed bandits when both projects vary." Journal of Applied Probability 26, no. 03 (September 1989): 655–58. http://dx.doi.org/10.1017/s0021900200038262.
Повний текст джерелаWang, 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.
Повний текст джерелаZuo, Jinhang, Xiaoxi Zhang, and Carlee Joe-Wong. "Observe Before Play: Multi-Armed Bandit with Pre-Observations." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 7023–30. http://dx.doi.org/10.1609/aaai.v34i04.6187.
Повний текст джерелаNamba, Hiroyuki. "Non-stationary Stochastic Multi-armed Bandit Problems with External Information on Stationarity." Transactions of the Japanese Society for Artificial Intelligence 36, no. 3 (May 1, 2021): D—K84_1–11. http://dx.doi.org/10.1527/tjsai.36-3_d-k84.
Повний текст джерелаAuer, Peter, and Ronald Ortner. "UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem." Periodica Mathematica Hungarica 61, no. 1-2 (September 2010): 55–65. http://dx.doi.org/10.1007/s10998-010-3055-6.
Повний текст джерелаNiño-Mora, José. "Multi-Gear Bandits, Partial Conservation Laws, and Indexability." Mathematics 10, no. 14 (July 18, 2022): 2497. http://dx.doi.org/10.3390/math10142497.
Повний текст джерелаOu, Mingdong, Nan Li, Cheng Yang, Shenghuo Zhu, and Rong Jin. "Semi-Parametric Sampling for Stochastic Bandits with Many Arms." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7933–40. http://dx.doi.org/10.1609/aaai.v33i01.33017933.
Повний текст джерелаFeldman, Zohar, and Carmel Domshlak. "On MABs and Separation of Concerns in Monte-Carlo Planning for MDPs." Proceedings of the International Conference on Automated Planning and Scheduling 24 (May 10, 2014): 120–27. http://dx.doi.org/10.1609/icaps.v24i1.13631.
Повний текст джерелаOttens, Brammert, Christos Dimitrakakis, and Boi Faltings. "DUCT: An Upper Confidence Bound Approach to Distributed Constraint Optimization Problems." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 528–34. http://dx.doi.org/10.1609/aaai.v26i1.8129.
Повний текст джерелаGuan, 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.
Повний текст джерелаCowan, Wesley, and Michael N. Katehakis. "EXPLORATION–EXPLOITATION POLICIES WITH ALMOST SURE, ARBITRARILY SLOW GROWING ASYMPTOTIC REGRET." Probability in the Engineering and Informational Sciences 34, no. 3 (January 26, 2019): 406–28. http://dx.doi.org/10.1017/s0269964818000529.
Повний текст джерелаNiño-Mora, José. "Markovian Restless Bandits and Index Policies: A Review." Mathematics 11, no. 7 (March 28, 2023): 1639. http://dx.doi.org/10.3390/math11071639.
Повний текст джерелаPapagiannis, Tasos, Georgios Alexandridis, and Andreas Stafylopatis. "Pruning Stochastic Game Trees Using Neural Networks for Reduced Action Space Approximation." Mathematics 10, no. 9 (May 1, 2022): 1509. http://dx.doi.org/10.3390/math10091509.
Повний текст джерелаGyörgy, A., and L. Kocsis. "Efficient Multi-Start Strategies for Local Search Algorithms." Journal of Artificial Intelligence Research 41 (July 29, 2011): 407–44. http://dx.doi.org/10.1613/jair.3313.
Повний текст джерелаTrovo, Francesco, Stefano Paladino, Marcello Restelli, and Nicola Gatti. "Sliding-Window Thompson Sampling for Non-Stationary Settings." Journal of Artificial Intelligence Research 68 (May 26, 2020): 311–64. http://dx.doi.org/10.1613/jair.1.11407.
Повний текст джерелаKillian, 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.
Повний текст джерелаWATANABE, Ryo, Junpei KOMIYAMA, Atsuyoshi NAKAMURA, and Mineichi KUDO. "KL-UCB-Based Policy for Budgeted Multi-Armed Bandits with Stochastic Action Costs." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E100.A, no. 11 (2017): 2470–86. http://dx.doi.org/10.1587/transfun.e100.a.2470.
Повний текст джерелаYoussef, Marie-Josepha, Venugopal V. Veeravalli, Joumana Farah, Charbel Abdel Nour, and Catherine Douillard. "Resource Allocation in NOMA-Based Self-Organizing Networks Using Stochastic Multi-Armed Bandits." IEEE Transactions on Communications 69, no. 9 (September 2021): 6003–17. http://dx.doi.org/10.1109/tcomm.2021.3092767.
Повний текст джерелаSledge, Isaac, and José Príncipe. "An Analysis of the Value of Information When Exploring Stochastic, Discrete Multi-Armed Bandits." Entropy 20, no. 3 (February 28, 2018): 155. http://dx.doi.org/10.3390/e20030155.
Повний текст джерелаPokhrel, Shiva Raj, and Michel Mandjes. "Internet of Drones: Improving Multipath TCP over WiFi with Federated Multi-Armed Bandits for Limitless Connectivity." Drones 7, no. 1 (December 31, 2022): 30. http://dx.doi.org/10.3390/drones7010030.
Повний текст джерелаPainter, Michael, Bruno Lacerda, and Nick Hawes. "Convex Hull Monte-Carlo Tree-Search." Proceedings of the International Conference on Automated Planning and Scheduling 30 (June 1, 2020): 217–25. http://dx.doi.org/10.1609/icaps.v30i1.6664.
Повний текст джерелаGasnikov, A. V., E. A. Krymova, A. A. Lagunovskaya, I. N. Usmanova, and F. A. Fedorenko. "Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case." Automation and Remote Control 78, no. 2 (February 2017): 224–34. http://dx.doi.org/10.1134/s0005117917020035.
Повний текст джерелаCiucanu, Radu, Pascal Lafourcade, Marius Lombard-Platet, and Marta Soare. "Secure protocols for cumulative reward maximization in stochastic multi-armed bandits." Journal of Computer Security, February 2, 2022, 1–27. http://dx.doi.org/10.3233/jcs-210051.
Повний текст джерелаAmakasu, Takashi, Nicolas Chauvet, Guillaume Bachelier, Serge Huant, Ryoichi Horisaki, and Makoto Naruse. "Conflict-free collective stochastic decision making by orbital angular momentum of photons through quantum interference." Scientific Reports 11, no. 1 (October 26, 2021). http://dx.doi.org/10.1038/s41598-021-00493-2.
Повний текст джерелаImmorlica, 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.
Повний текст джерелаZhou, 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.
Повний текст джерелаFernandez-Tapia, Joaquin, and Charles Monzani. "Stochastic Multi-Armed Bandit Algorithm for Optimal Budget Allocation in Programmatic Advertising." SSRN Electronic Journal, 2015. http://dx.doi.org/10.2139/ssrn.2600473.
Повний текст джерелаGopalan, Aditya, Prashanth L. A., Michael Fu, and Steve Marcus. "Weighted Bandits or: How Bandits Learn Distorted Values That Are Not Expected." Proceedings of the AAAI Conference on Artificial Intelligence 31, no. 1 (February 13, 2017). http://dx.doi.org/10.1609/aaai.v31i1.10922.
Повний текст джерелаMandel, Travis, Yun-En Liu, Emma Brunskill, and Zoran Popović. "The Queue Method: Handling Delay, Heuristics, Prior Data, and Evaluation in Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 29, no. 1 (February 21, 2015). http://dx.doi.org/10.1609/aaai.v29i1.9604.
Повний текст джерелаLiu, Fang, Swapna Buccapatnam, and Ness Shroff. "Information Directed Sampling for Stochastic Bandits With Graph Feedback." Proceedings of the AAAI Conference on Artificial Intelligence 32, no. 1 (April 29, 2018). http://dx.doi.org/10.1609/aaai.v32i1.11751.
Повний текст джерелаHashima, Sherief, Mostafa M. Fouda, Sadman Sakib, Zubair Md Fadlullah, Kohei Hatano, Ehab Mahmoud Mohamed, and Xuemin Shen. "Energy-Aware Hybrid RF-VLC Multi-Band Selection in D2D Communication: A Stochastic Multi-Armed Bandit Approach." IEEE Internet of Things Journal, 2022, 1. http://dx.doi.org/10.1109/jiot.2022.3162135.
Повний текст джерелаLi, Bo, and Chi Ho Yeung. "Understanding the stochastic dynamics of sequential decision-making processes: A path-integral analysis of multi-armed bandits." Chaos: An Interdisciplinary Journal of Nonlinear Science 33, no. 6 (June 1, 2023). http://dx.doi.org/10.1063/5.0120076.
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