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» Approximate Expectation Maximization
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108
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NIPS
2007
15 years 5 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
116
Voted
EACL
2006
ACL Anthology
15 years 5 months ago
Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis
Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
Ayman Farahat, Francine Chen
129
Voted
IMAGING
2004
15 years 4 months ago
Extending Printing Color Gamut by Optimizing the Spectral Reflectance of Inks
A computer simulation was performed to investigate the optimum combinations of three- and four-chromatic inks in order to maximize the color gamut for halftone printing. A virtual...
Yongda Chen, Roy S. Berns, Lawrence A. Taplin
102
Voted
NIPS
1998
15 years 4 months ago
Convergence of the Wake-Sleep Algorithm
The W-S (Wake-Sleep) algorithm is a simple learning rule for the models with hidden variables. It is shown that this algorithm can be applied to a factor analysis model which is a...
Shiro Ikeda, Shun-ichi Amari, Hiroyuki Nakahara
124
Voted
NIPS
2000
15 years 4 months ago
Algorithms for Non-negative Matrix Factorization
Non-negative matrix factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. Two different multiplicative algorithms for NMF are analyzed....
Daniel D. Lee, H. Sebastian Seung