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ICML
2003
IEEE
16 years 4 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...
ICMCS
2005
IEEE
105views Multimedia» more  ICMCS 2005»
15 years 9 months ago
Speech-Based Visual Concept Learning Using Wordnet
Modeling visual concepts using supervised or unsupervised machine learning approaches are becoming increasing important for video semantic indexing, retrieval, and filtering appli...
Xiaodan Song, Ching-Yung Lin, Ming-Ting Sun
PAMI
2010
276views more  PAMI 2010»
15 years 2 months ago
Local-Learning-Based Feature Selection for High-Dimensional Data Analysis
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
Yijun Sun, Sinisa Todorovic, Steve Goodison
CIVR
2003
Springer
126views Image Analysis» more  CIVR 2003»
15 years 9 months ago
Learning in Region-Based Image Retrieval
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to region-based image retrieval (RBIR). First, the query point m...
Feng Jing, Mingjing Li, Lei Zhang, HongJiang Zhang...
ACL
1998
15 years 5 months ago
Dialogue Act Tagging with Transformation-Based Learning
For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract valu...
Ken Samuel, Sandra Carberry, K. Vijay-Shanker