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ECCC
2007
180views more  ECCC 2007»
13 years 4 months ago
Adaptive Algorithms for Online Decision Problems
We study the notion of learning in an oblivious changing environment. Existing online learning algorithms which minimize regret are shown to converge to the average of all locally...
Elad Hazan, C. Seshadhri
AAAI
2007
13 years 7 months ago
An Ironing-Based Approach to Adaptive Online Mechanism Design in Single-Valued Domains
Online mechanism design considers the problem of sequential decision making in a multi-agent system with self-interested agents. The agent population is dynamic and each agent has...
David C. Parkes, Quang Duong
COLT
2003
Springer
13 years 10 months ago
Efficient Algorithms for Online Decision Problems
Adam Kalai, Santosh Vempala
COLT
2008
Springer
13 years 6 months ago
Regret Bounds for Sleeping Experts and Bandits
We study on-line decision problems where the set of actions that are available to the decision algorithm vary over time. With a few notable exceptions, such problems remained larg...
Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yo...
ICPR
2008
IEEE
14 years 6 months ago
Training sequential on-line boosting classifier for visual tracking
On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
Helmut Grabner, Horst Bischof, Jan Sochman, Jiri M...