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ICMLC
2005
Springer
15 years 3 months ago
Kernel-Based Metric Adaptation with Pairwise Constraints
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
Hong Chang, Dit-Yan Yeung
ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
15 years 3 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
87
Voted
JMLR
2010
123views more  JMLR 2010»
14 years 4 months ago
Inductive Principles for Restricted Boltzmann Machine Learning
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
Benjamin Marlin, Kevin Swersky, Bo Chen, Nando de ...
70
Voted
ICML
2008
IEEE
15 years 10 months ago
Classification using discriminative restricted Boltzmann machines
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
Hugo Larochelle, Yoshua Bengio
89
Voted
AI50
2006
15 years 1 months ago
Intrinsically Motivated Machines
Abstract. Children seem intrinsically motivated to manipulate, to explore, to test, to learn and they look for activities and situations that provide such learning opportunities. I...
Frédéric Kaplan, Pierre-Yves Oudeyer