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» Learning and Generalization with the Information Bottleneck
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SOFSEM
2010
Springer
16 years 3 months ago
Regret Minimization and Job Scheduling
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Yishay Mansour
UAI
2004
15 years 8 months ago
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Omid Madani, Daniel J. Lizotte, Russell Greiner
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
16 years 7 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
MM
2004
ACM
178views Multimedia» more  MM 2004»
16 years 1 hour ago
A bootstrapping framework for annotating and retrieving WWW images
Most current image retrieval systems and commercial search engines use mainly text annotations to index and retrieve WWW images. This research explores the use of machine learning...
HuaMin Feng, Rui Shi, Tat-Seng Chua
SIGECOM
2011
ACM
259views ECommerce» more  SIGECOM 2011»
14 years 9 months ago
Designing adaptive trading agents
ended abstract summarizes the research presented in Dr. Pardoe’s recently-completed Ph.D. thesis [Pardoe 2011]. The thesis considers how adaptive trading agents can take advantag...
David Pardoe, Peter Stone