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» Sampling Methods for Unsupervised Learning
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109
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NIPS
2004
15 years 4 months ago
Semi-supervised Learning by Entropy Minimization
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...
Yves Grandvalet, Yoshua Bengio
133
Voted
ICMCS
2005
IEEE
111views Multimedia» more  ICMCS 2005»
15 years 8 months ago
Manifold learning, a promised land or work in progress?
ABSTRACT In this paper, we report our experiments using a realworld image dataset to examine the effectiveness of Isomap, LLE and KPCA. The 1,897-image dataset we used consists of ...
Mei-Chen Yeh, I-Hsiang Lee, Gang Wu, Yi Wu, Edward...
130
Voted
SIGIR
2011
ACM
14 years 5 months ago
Parameterized concept weighting in verbose queries
The majority of the current information retrieval models weight the query concepts (e.g., terms or phrases) in an unsupervised manner, based solely on the collection statistics. I...
Michael Bendersky, Donald Metzler, W. Bruce Croft
112
Voted
AAAI
2008
15 years 5 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small
129
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Speech modeling based on committee-based active learning
We propose a committee-based active learning method for large vocabulary continuous speech recognition. In this approach, multiple recognizers are prepared beforehand, and the rec...
Yuzu Hamanaka, Koichi Shinoda, Sadaoki Furui, Tada...