1731 search results - page 29 / 347 » Maximum likelihood analysis of algorithms and data structure... |
ICPR
2008
IEEE
14 years 2 months ago
2008
IEEE
We propose new Continuous Hidden Markov Model (CHMM) structure that integrates feature weighting component. We assume that each feature vector could include different subsets of f...
NIPS
2003
13 years 9 months ago
2003
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...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, p...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
ICONIP
2007
13 years 9 months ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...