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» Information Extraction with HMM Structures Learned by Stocha...
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113
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ISNN
2007
Springer
15 years 8 months ago
Neural-Based Separating Method for Nonlinear Mixtures
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
Ying Tan
EMNLP
2010
14 years 11 months ago
Multi-Level Structured Models for Document-Level Sentiment Classification
In this paper, we investigate structured models for document-level sentiment classification. When predicting the sentiment of a subjective document (e.g., as positive or negative)...
Ainur Yessenalina, Yisong Yue, Claire Cardie
NIPS
2007
15 years 3 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
WWW
2009
ACM
16 years 2 months ago
Extracting article text from the web with maximum subsequence segmentation
Much of the information on the Web is found in articles from online news outlets, magazines, encyclopedias, review collections, and other sources. However, extracting this content...
Jeff Pasternack, Dan Roth
105
Voted
ICML
2004
IEEE
16 years 2 months ago
A needle in a haystack: local one-class optimization
This paper addresses the problem of finding a small and coherent subset of points in a given data. This problem, sometimes referred to as one-class or set covering, requires to fi...
Koby Crammer, Gal Chechik