Results 31 to 40 of about 1,303 (127)
Differential Privacy in Social Networks Using Multi-Armed Bandit
IEEE Access, 2022 There has been an exponential growth over the years in the number of users connected to social networks. This has spurred research interest in social networks to ensure the privacy of users. From a theoretical standpoint, a social network is modeled as a
Olusola T. Odeyomi
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Addictive Games: Case Study on Multi-Armed Bandit Game
Information, 2021 The attraction of games comes from the player being able to have fun in games. Gambling games that are based on the Variable-Ratio schedule in Skinner’s experiment are the most typical addictive games.
Xiaohan Kang +3 more
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“Caught in a Trap”: Everyday Peace and the Dilemma of Representation in Rio de Janeiro
City &Society, Volume 38, Issue 2, August 2026.ABSTRACT Urban security interventions often seek legitimacy by changing how places associated with violence are publicly represented. Less attention has been paid to how grassroots organizations navigate these representational pressures as they pursue everyday peace.
Henry Staples, Sarah Vogelsanger
wiley +1 more source
Multi-Dimensional Arms for Combinatorial Multi-Armed Bandit
IEEE AccessThe multi-armed bandit (MAB) problem with concave rewards has indeed become a significant area of research in recent years. In MAB problem, maximizing total rewards within a fixed number of pulls is a common objective.
Qi Li, Lijun Cai
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Mean‐Variance Payoff Applied to Stackelberg Games
Mathematical Methods in the Applied Sciences, Volume 49, Issue 10, Page 11516-11533, 15 July 2026.ABSTRACT We analyse a Stackelberg duopoly in which the leader faces uncertainty about the intercept demand, while the follower observes the realised demand and decides whether to enter the market after the uncertainty is resolved. The leader evaluates the uncertainty by maximising a mean‐variance utility function that captures its risk aversion.
João M. Silva +3 more
wiley +1 more source
Comparison of Video Recommendation Effects of Etc, Ucb, and Thompson Sampling Algorithms on Short-Video Platforms [PDF]
ITM Web of ConferencesThis paper comprehensively compares the performance of three multi-armed bandit (MAB) algorithms, Epsilon-Then-Commit (ETC), upper confidence bound (UCB), and Thompson sampling (TS), for video recommendation in dynamic environments.
Li Shouchuan
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International Journal of Imaging Systems and Technology, Volume 36, Issue 4, July 2026.ABSTRACT Gliomas are aggressive brain tumors that require accurate imaging‐based diagnosis, where automated segmentation plays a central role in assessing tumor morphology and guiding treatment decisions. Manual delineation of gliomas is time‐consuming and prone to variability, motivating the use of deep learning to improve consistency and alleviate ...
Cecilia Diana‐Albelda +4 more
wiley +1 more source
Multi-Armed Bandits Convergence Acceleration Using Cluster Normalizations
IEEE AccessRecommender systems usually operate in non-stationary environments, so the standard techniques used to create recommendations begin to degrade after some use.
Victoria Strenadko +2 more
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IEEE Access, 2019 In order to enhance the anti-jamming capability of aeronautic swarm tactical network in the complicated electromagnetic environment, we address the problem of bandit-based cognitive anti-jamming strategy for enabling reliable information transmission. We
Haitao Li, Jiawei Luo, Changjun Liu
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Disasters, Volume 50, Issue 3, July 2026.Abstract Are social networks the key to understanding resilience in conflict? Recent studies suggest so, but relational research in conflict‐affected areas is rare. What exists stresses the importance of small circles of close family members, trusted friends, and co‐ethnic persons/groups, but tends to overlook their aggregate effect.
Solange G. Fontana
wiley +1 more source