Sciweavers

Share
15 search results - page 2 / 3
» Online Algorithms for the Multi-Armed Bandit Problem with Ma...
Sort
View
CORR
2008
Springer
136views Education» more  CORR 2008»
9 years 5 months ago
Multi-Armed Bandits in Metric Spaces
In a multi-armed bandit problem, an online algorithm chooses from a set of strategies in a sequence of n trials so as to maximize the total payoff of the chosen strategies. While ...
Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal
CORR
2010
Springer
171views Education» more  CORR 2010»
9 years 14 days ago
Online Learning in Opportunistic Spectrum Access: A Restless Bandit Approach
We consider an opportunistic spectrum access (OSA) problem where the time-varying condition of each channel (e.g., as a result of random fading or certain primary users' activ...
Cem Tekin, Mingyan Liu
FOCS
2007
IEEE
9 years 12 months ago
Approximation Algorithms for Partial-Information Based Stochastic Control with Markovian Rewards
We consider a variant of the classic multi-armed bandit problem (MAB), which we call FEEDBACK MAB, where the reward obtained by playing each of n independent arms varies according...
Sudipto Guha, Kamesh Munagala
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
9 years 10 months ago
Toward comparison-based adaptive operator selection
Adaptive Operator Selection (AOS) turns the impacts of the applications of variation operators into Operator Selection through a Credit Assignment mechanism. However, most Credit ...
Álvaro Fialho, Marc Schoenauer, Michè...
SAC
2005
ACM
9 years 11 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classi´Čüers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
books