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ICML
2006
IEEE
14 years 8 months ago
Robust probabilistic projections
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...
Cédric Archambeau, Michel Verleysen, Nicola...
NIPS
2008
13 years 9 months ago
Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction
We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
Shay B. Cohen, Kevin Gimpel, Noah A. Smith
CONCUR
1994
Springer
13 years 11 months ago
Composition and Behaviors of Probabilistic I/O Automata
We augment the I/O automaton model of Lynch and Tuttle with probability, as a step toward the ultimate goal of obtaining a useful tool for specifying and reasoning about asynchron...
Sue-Hwey Wu, Scott A. Smolka, Eugene W. Stark
SIGIR
2004
ACM
14 years 1 months ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny
EMNLP
2006
13 years 9 months ago
Extremely Lexicalized Models for Accurate and Fast HPSG Parsing
This paper describes an extremely lexicalized probabilistic model for fast and accurate HPSG parsing. In this model, the probabilities of parse trees are defined with only the pro...
Takashi Ninomiya, Takuya Matsuzaki, Yoshimasa Tsur...