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DAGSTUHL
2009
13 years 8 months ago
Statistical Mechanics of On-line Learning
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...
Michael Biehl, Nestor Caticha, Peter Riegler
IJHPCA
2008
66views more  IJHPCA 2008»
13 years 7 months ago
Efficient Parallel I/O in Community Atmosphere Model (CAM)
pc.sagepub.com/cgi/content/abstract/22/2/206 The online version of this article can be found at: Published by: http://www.sagepublications.com can be found at:International Journal...
Yu-Heng Tseng, Chris H. Q. Ding
CVPR
2008
IEEE
14 years 9 months ago
Boosting adaptive linear weak classifiers for online learning and tracking
Online boosting methods have recently been used successfully for tracking, background subtraction etc. Conventional online boosting algorithms emphasize on interchanging new weak ...
Toufiq Parag, Fatih Porikli, Ahmed M. Elgammal
COLT
2008
Springer
13 years 9 months ago
Extracting Certainty from Uncertainty: Regret Bounded by Variation in Costs
Prediction from expert advice is a fundamental problem in machine learning. A major pillar of the field is the existence of learning algorithms whose average loss approaches that ...
Elad Hazan, Satyen Kale
CE
2004
88views more  CE 2004»
13 years 7 months ago
Beyond formal learning: Informal community eLearning
The goal of the study described in this paper was to gain an improved understanding of the social context of UK online centres and issues around the creation and exchange of knowl...
John Cook, Matt Smith