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119
Voted
CVPR
2010
IEEE
15 years 1 months ago
2010
IEEE
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
115
Voted
CVPR
2009
IEEE
16 years 5 months ago
2009
IEEE
Graph-based methods form a main category of semisupervised
learning, offering flexibility and easy implementation
in many applications. However, the performance of
these methods...
NIPS
2004
14 years 11 months ago
2004
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
91
Voted
COLT
2008
Springer
15 years 1 days ago
2008
Springer
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
84
Voted
GECCO
2006
Springer
15 years 1 months ago
2006
Springer
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...