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» Implicit Online Learning
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COLT
1999
Springer
15 years 9 months ago
On a Generalized Notion of Mistake Bounds
This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...
Sanjay Jain, Arun Sharma
KES
2005
Springer
15 years 10 months ago
User Preference Learning for Multimedia Personalization in Pervasive Computing Environment
Pervasive computing environment and users’ demand for multimedia personalization precipitate a need for personalization tools to help people access desired multimedia content at ...
Zhiwen Yu, Daqing Zhang, Xingshe Zhou, Changde Li
141
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COLT
2006
Springer
15 years 8 months ago
Online Variance Minimization
We design algorithms for two online variance minimization problems. Specifically, in every trial t our algorithms get a covariance matrix Ct and try to select a parameter vector wt...
Manfred K. Warmuth, Dima Kuzmin
ESANN
2004
15 years 6 months ago
Online policy adaptation for ensemble classifiers
Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of usin...
Christos Dimitrakakis, Samy Bengio
EPIA
2009
Springer
15 years 11 months ago
Classifying Documents According to Locational Relevance
This paper presents an approach for categorizing documents according to their implicit locational relevance. We report a thorough evaluation of several classifiers designed for th...
Ivo Anastácio, Bruno Martins, Pável ...