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159
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ICCV
2009
IEEE
16 years 9 months ago
Is that you? Metric Learning Approaches for Face Identification
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background...
Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmi...
153
Voted
AMAI
2004
Springer
15 years 10 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
135
Voted
ECML
2007
Springer
15 years 10 months ago
Decision Tree Instability and Active Learning
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable – they can produce drastic...
Kenneth Dwyer, Robert Holte
166
Voted
AAAI
2000
15 years 6 months ago
Self-Supervised Learning for Visual Tracking and Recognition of Human Hand
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...
Ying Wu, Thomas S. Huang
112
Voted
ACL
1998
15 years 6 months ago
Building Accurate Semantic Taxonomies from Monolingual MRDs
This paper presents a method that conbines a set of unsupervised algorithms in order to accurately build large taxonomies from any machine-readable dictionary (MRD). Our aim is to...
German Rigau, Eneko Agirre