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COLT
2008
Springer
13 years 12 months ago
Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization
We introduce an efficient algorithm for the problem of online linear optimization in the bandit setting which achieves the optimal O ( T) regret. The setting is a natural general...
Jacob Abernethy, Elad Hazan, Alexander Rakhlin
TC
2010
13 years 4 months ago
SALSA: Strategyproof Online Spectrum Admissions for Wireless Networks
It is imperative to design efficient and effective online spectrum allocation methods since requests for spectrums often come in an online fashion. In this paper, we propose SALSA,...
Ping Xu, ShiGuang Wang, Xiang-Yang Li
ATAL
2009
Springer
14 years 4 months ago
Online exploration in least-squares policy iteration
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
ECCV
2008
Springer
14 years 12 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
ICML
2003
IEEE
14 years 11 months ago
Online Feature Selection using Grafting
In the standard feature selection problem, we are given a fixed set of candidate features for use in a learning problem, and must select a subset that will be used to train a mode...
Simon Perkins, James Theiler