Sciweavers

263 search results - page 6 / 53
» Regret Bounds for Prediction Problems
Sort
View
CORR
2010
Springer
112views Education» more  CORR 2010»
13 years 4 months ago
Optimal Distributed Online Prediction using Mini-Batches
Online prediction methods are typically presented as serial algorithms running on a single processor. However, in the age of web-scale prediction problems, it is increasingly comm...
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir, Lin X...
ML
2002
ACM
133views Machine Learning» more  ML 2002»
13 years 7 months ago
Finite-time Analysis of the Multiarmed Bandit Problem
Reinforcement learning policies face the exploration versus exploitation dilemma, i.e. the search for a balance between exploring the environment to find profitable actions while t...
Peter Auer, Nicolò Cesa-Bianchi, Paul Fisch...
COLT
2007
Springer
14 years 1 months ago
Improved Rates for the Stochastic Continuum-Armed Bandit Problem
Abstract. Considering one-dimensional continuum-armed bandit problems, we propose an improvement of an algorithm of Kleinberg and a new set of conditions which give rise to improve...
Peter Auer, Ronald Ortner, Csaba Szepesvári
CORR
2010
Springer
55views Education» more  CORR 2010»
13 years 7 months ago
Prediction with Advice of Unknown Number of Experts
In the framework of prediction with expert advice, we consider a recently introduced kind of regret bounds: the bounds that depend on the effective instead of nominal number of ex...
Alexey V. Chernov, Vladimir Vovk
NIPS
2008
13 years 8 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari