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ML
1998
ACM
102views Machine Learning» more  ML 1998»
14 years 9 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha
EPIA
2003
Springer
15 years 2 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas
DAGSTUHL
2009
14 years 10 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
MM
2004
ACM
124views Multimedia» more  MM 2004»
15 years 2 months ago
An online-optimized incremental learning framework for video semantic classification
This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Jun Wu, Xian-Sheng Hua, HongJiang Zhang, Bo Zhang
WWW
2009
ACM
15 years 10 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel