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NIPS
2003
13 years 11 months ago
Non-linear CCA and PCA by Alignment of Local Models
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis
NIPS
2003
13 years 11 months ago
Extreme Components Analysis
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
Max Welling, Felix V. Agakov, Christopher K. I. Wi...
SDM
2003
SIAM
129views Data Mining» more  SDM 2003»
13 years 11 months ago
Approximate Query Answering by Model Averaging
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
Dmitry Pavlov, Padhraic Smyth
AAAI
1998
13 years 11 months ago
Bayesian Q-Learning
A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...
Richard Dearden, Nir Friedman, Stuart J. Russell
AAAI
1998
13 years 11 months ago
Modeling Web Sources for Information Integration
The Web is based on a browsing paradigm that makes it di cult to retrieve and integrate data from multiple sites. Today, the only way to do this is to build specialized applicatio...
Craig A. Knoblock, Steven Minton, José Luis...
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