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FOCS
1990
IEEE
15 years 10 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
ICASSP
2010
IEEE
15 years 6 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock
ICML
2009
IEEE
16 years 1 months ago
Independent factor topic models
Topic models such as Latent Dirichlet Allocation (LDA) and Correlated Topic Model (CTM) have recently emerged as powerful statistical tools for text document modeling. In this pap...
Duangmanee Putthividhya, Hagai Thomas Attias, Srik...
ECML
2003
Springer
15 years 12 months ago
A Hybrid Language Model based on Stochastic Context-free Grammars
Abstract. This paper explores the use of initial Stochastic Context-Free Grammars (SCFG) obtained from a treebank corpus for the learning of SCFG by means of estimation algorithms....
Diego Linares, José-Miguel Benedí, J...
ECML
2007
Springer
16 years 24 days ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani