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AAAI
2010
13 years 8 months ago
Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
Ian Porteous, Arthur Asuncion, Max Welling
NN
2008
Springer
201views Neural Networks» more  NN 2008»
13 years 6 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio
AAAI
2006
13 years 8 months ago
Fast Hierarchical Goal Schema Recognition
We present our work on using statistical, corpus-based machine learning techniques to simultaneously recognize an agent's current goal schemas at various levels of a hierarch...
Nate Blaylock, James F. Allen
ICIS
2003
13 years 8 months ago
A Computational Approach to Compare Information Revelation Policies
Revelation policies in an e-marketplace differ in terms of the level of competitive information disseminated to participating sellers. Since sellers who repeatedly compete against...
Amy R. Greenwald, Karthik Kannan, Ramayya Krishnan
RECOMB
2007
Springer
14 years 7 months ago
A Bayesian Model That Links Microarray mRNA Measurements to Mass Spectrometry Protein Measurements
Abstract. An important problem in biology is to understand correspondences between mRNA microarray levels and mass spectrometry peptide counts. Recently, a compendium of mRNA expre...
Anitha Kannan, Andrew Emili, Brendan J. Frey