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TCS
2010
13 years 6 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
ICTAI
2002
IEEE
14 years 15 days ago
Machine Learning for Software Engineering: Case Studies in Software Reuse
There are many machine learning algorithms currently available. In the 21st century, the problem no longer lies in writing the learner, but in choosing which learners to run on a ...
Justin S. Di Stefano, Tim Menzies
CG
2000
Springer
13 years 12 months ago
Chess Neighborhoods, Function Combination, and Reinforcement Learning
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
Robert Levinson, Ryan Weber
TOIS
2010
128views more  TOIS 2010»
13 years 6 months ago
Learning author-topic models from text corpora
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
CVPR
2009
IEEE
15 years 2 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...