Results 171 to 180 of about 3,144 (205)

Adaptive bandit algorithms increase efficiency of mobile tuberculosis screening programs. [PDF]

Sci Rep
Zhang J, Linde L, Puma D, Millones AK, Tintaya K, Jimenez J, Jenkins HE, Becerra MC, Keshavjee S, Lecca L, Cutkosky A, Brooks MB.   +11 more
europepmc   +1 more source

Effects of Early Adversity and War Trauma on Learning Under Uncertainty. [PDF]

Dev Sci
Lisi M, Michalek J, Hadfield K, Dajani R, Mareschal I.   +4 more
europepmc   +1 more source

DMSTG-AD: an SDN intrusion detection method based on dynamic multi-scale spatio-temporal graph neural network. [PDF]

Sci Rep
Zhao J, Zhang D, He Q, Lin M, Yang Y.
europepmc   +1 more source

Advanced Reinforcement Learning Algorithms for Multi-Armed Bandit Problems

Francisco Robledo Relaño
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Secure Outsourcing of Multi-armed Bandits

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2020
We consider the problem of cumulative reward maximization in multi-armed bandits. We address the security concerns that occur when data and computations are outsourced to an honest-but-curious cloud i.e., that executes tasks dutifully, but tries to gain as much information as possible.
Ciucanu, Radu, Lafourcade, Pascal, Lombard-Platet, Marius, Soare, Marta   +3 more
openaire   +2 more sources

The Multi-Armed Bandit With Stochastic Plays

IEEE Transactions on Automatic Control, 2018
We extend the stochastic multi-armed bandit to the case where the number of arms to play evolves as a stationary process. Our work is motivated by demand response in power systems, in which the number of arms to play, or loads to dispatch, depends on a random power imbalance.
Antoine Lesage-Landry, Joshua A. Taylor
openaire   +2 more sources

On optimal foraging and multi-armed bandits

2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2013
We consider two variants of the standard multi-armed bandit problem, namely, the multi-armed bandit problem with transition costs and the multi-armed bandit problem on graphs. We develop block allocation algorithms for these problems that achieve an expected cumulative regret that is uniformly dominated by a logarithmic function of time, and an ...
Vaibhav Srivastava, Paul Reverdy, Naomi Ehrich Leonard   +2 more
openaire   +1 more source

Multi-Armed Bandits With Costly Probes

IEEE Transactions on Information Theory
Multi-armed bandits is a sequential decision-making problem where an agent must choose between multiple actions to maximize its cumulative reward over time, while facing uncertainty about the rewards associated with each action. The challenge lies in balancing the exploration of potentially higher-rewarding actions with the exploitation of known high ...
Eray Can Elumar, Cem Tekin, Osman Yagan
openaire   +2 more sources

Compression for Multi-Arm Bandits

IEEE Journal on Selected Areas in Information Theory, 2022
Osama A. Hanna, Lin F. Yang, Christina Fragouli   +2 more
openaire   +1 more source