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probability theory and machine learning, the multi-armed bandit problem (sometimes called the K- or N-armed bandit problem) is a problem in which a decision...

problems concerning the scheduling of a batch of stochastic jobs, multi-armed bandit problems, and problems concerning the scheduling of queueing systems...

expected reward." He then moves on to the "Multi–armed bandit problem" where each pull on a "one armed bandit" lever is allocated a reward function for...

swaps of medoids and non-medoids using sampling. BanditPAM uses the concept of multi-armed bandits to choose candidate swaps instead of uniform sampling...

include developing minimax rate for multi-armed bandits, linear bandits, developing an optimal algorithm for bandit convex optimization, and solving long-standing...

actions that address the exploration-exploitation dilemma in the multi-armed bandit problem. It consists of choosing the action that maximizes the expected...

lemons and cherries. Slot machines are also known pejoratively as "one-armed bandits", alluding to the large mechanical levers affixed to the sides of early...

"I Am a Sword" The Bandits, an English blues band Bandits (Belgian band), a Belgian band Bandit (band), a British rock band "Bandit" (Juice Wrld and YoungBoy...

Sebastian; Shomorony, Ilan (2020). "BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits". arXiv:2006.06856 [cs.LG]. Zhang, Yan;...

noted for his work in Markov decision process, Gittins index, the multi-armed bandit, Markov chains and other related fields. Katehakis was born and grew...

interval method, an AI method used in Monte Carlo tree search & multi-armed bandits Search for "ucb"  or "u-c-b" on Wikipedia. All pages with titles...

recommendations. Note: one commonly implemented solution to this problem is the multi-armed bandit algorithm. Scalability: There are millions of users and products in...

a unique white blood cell Multi-armed bandit, a problem in probability theory Queen Mab, a fairy in English literature Multi-author blog Yutanduchi Mixteco...

make good use of resources of all types. An example of this is the multi-armed bandit problem. Exploratory analysis of Bayesian models is an adaptation...

Another cutting-edge technique in field experiments is the use of the multi armed bandit design, including similar adaptive designs on experiments with variable...

learning, this is known as the exploration-exploitation trade-off (e.g. Multi-armed bandit#Empirical motivation). Dual control theory was developed by Alexander...

parameter-based feature extraction algorithms in computer vision. Multi-armed bandit Kriging Thompson sampling Global optimization Bayesian experimental...

Adaptive control Between-group design experiment Choice modelling Multi-armed bandit Multivariate testing Randomized controlled trial Scientific control...

for her work in stochastic optimization, compressed sensing, and multi-armed bandit problems. She works in Germany as a professor at Otto von Guericke...

is obtained by rearranging the terms. In multi-armed bandit, a lower bound on the minimax regret of any bandit algorithm can be proved using Bretagnolle–Huber...