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NIPS
2001
15 years 6 months ago
The Infinite Hidden Markov Model
We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integ...
Matthew J. Beal, Zoubin Ghahramani, Carl Edward Ra...
NIPS
2003
15 years 6 months ago
Computing Gaussian Mixture Models with EM Using Equivalence Constraints
Density estimation with Gaussian Mixture Models is a popular generative technique used also for clustering. We develop a framework to incorporate side information in the form of e...
Noam Shental, Aharon Bar-Hillel, Tomer Hertz, Daph...
JMLR
2010
134views more  JMLR 2010»
14 years 11 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
143
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EMNLP
2007
15 years 6 months ago
Syntactic Re-Alignment Models for Machine Translation
We present a method for improving word alignment for statistical syntax-based machine translation that employs a syntactically informed alignment model closer to the translation m...
Jonathan May, Kevin Knight
ICASSP
2010
IEEE
15 years 4 months ago
A union of incoherent spaces model for classification
We present a new and computationally efficient scheme for classifying signals into a fixed number of known classes. We model classes as subspaces in which the corresponding data...
Karin Schnass, Pierre Vandergheynst