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78
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ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 5 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
91
Voted
ICML
2004
IEEE
16 years 1 months ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
95
Voted
ISMB
1993
15 years 1 months ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
92
Voted
BC
2002
108views more  BC 2002»
15 years 13 days ago
Spike-timing-dependent plasticity: common themes and divergent vistas
Abstract. Recent experimental observations of spiketiming-dependent synaptic plasticity (STDP) have revitalized the study of synaptic learning rules. The most surprising aspect of ...
Ádám Kepecs, Mark C. W. van Rossum, ...
119
Voted
ROBOCUP
2005
Springer
134views Robotics» more  ROBOCUP 2005»
15 years 6 months ago
Simultaneous Learning to Acquire Competitive Behaviors in Multi-agent System Based on Modular Learning System
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments. A typical example is a case of RoboCup...
Yasutake Takahashi, Kazuhiro Edazawa, Kentarou Nom...