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» On learning algorithm selection for classification
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ICML
2003
IEEE
16 years 7 months ago
Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
Wee Sun Lee, Bing Liu
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 10 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
IJMMS
2008
80views more  IJMMS 2008»
15 years 6 months ago
Real-time classification of evoked emotions using facial feature tracking and physiological responses
We present automated, real-time models built with machine learning algorithms which use videotapes of subjects' faces in conjunction with physiological measurements to predic...
Jeremy N. Bailenson, Emmanuel D. Pontikakis, Iris ...
ICML
2009
IEEE
16 years 7 months ago
More generality in efficient multiple kernel learning
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
Manik Varma, Bodla Rakesh Babu
COLT
1992
Springer
15 years 10 months ago
Learning Switching Concepts
We consider learning in situations where the function used to classify examples may switch back and forth between a small number of different concepts during the course of learnin...
Avrim Blum, Prasad Chalasani