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» Sampling Methods for Unsupervised Learning
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ICML
2001
IEEE
15 years 12 months ago
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other popular techniques that instead aim to reduce versio...
Nicholas Roy, Andrew McCallum
110
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IJCNN
2000
IEEE
15 years 3 months ago
Unsupervised Learning of Neural Network Ensembles for Image Classification
In the field of pattern recognition, the combination of an ensemble of neural networks has been proposed as an approach to the development of high performance image classification...
Giorgio Giacinto, Fabio Roli, Giorgio Fumera
EMNLP
2004
15 years 13 days ago
Unsupervised WSD based on Automatically Retrieved Examples: The Importance of Bias
This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the "WordNet monosemous relatives" method t...
Eneko Agirre, David Martínez
NLPRS
2001
Springer
15 years 3 months ago
A Maximum Entropy Tagger with Unsupervised Hidden Markov Models
We describe a new tagging model where the states of a hidden Markov model (HMM) estimated by unsupervised learning are incorporated as the features in a maximum entropy model. Our...
Jun'ichi Kazama, Yusuke Miyao, Jun-ichi Tsujii
BIBE
2001
IEEE
188views Bioinformatics» more  BIBE 2001»
15 years 2 months ago
Interrelated Two-way Clustering: An Unsupervised Approach for Gene Expression Data Analysis
DNA arrays can be used to measure the expression levels of thousands of genes simultaneously. Currently most research focuses on the interpretation of the meaning of the data. How...
Chun Tang, Li Zhang, Aidong Zhang, Murali Ramanath...