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COLT
2008
Springer
15 years 5 months ago
Learning in the Limit with Adversarial Disturbances
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
Constantine Caramanis, Shie Mannor
138
Voted
HIS
2004
15 years 5 months ago
An Empirical Performance Comparison of Machine Learning Methods for Spam E-Mail Categorization
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...
Chih-Chin Lai, Ming-Chi Tsai
129
Voted
ICML
2009
IEEE
15 years 1 months ago
Multiple indefinite kernel learning with mixed norm regularization
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...
142
Voted
TCAD
2010
103views more  TCAD 2010»
14 years 10 months ago
Supervised Learning Based Power Management for Multicore Processors
- This paper presents a supervised learning based power management framework for a multi-processor system, where a power manager (PM) learns to predict the system performance state...
Hwisung Jung, Massoud Pedram
161
Voted
EDM
2010
248views Data Mining» more  EDM 2010»
15 years 5 months ago
Analyzing Learning Styles using Behavioral Indicators in Web based Learning Environments
It is argued that the analysis of the learner's generated log files during interactions with a learning environment is necessary to produce interpretative views of their activ...
Nabila Bousbia, Jean-Marc Labat, Amar Balla, Issam...