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» Theory and Use of the EM Algorithm
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ICIP
2003
IEEE
14 years 1 months ago
Parameter estimation for spatial random trees using the EM algorithm
A new class of multiscale multidimensional stochastic processes called spatial random trees was recently introduced in [9]. The model is based on multiscale stochastic trees with ...
Ilya Pollak, Jeffrey Mark Siskind, Mary P. Harper,...
NLPRS
2001
Springer
14 years 1 months ago
A Separate-and-Learn Approach to EM Learning of PCFGs
WeproposeanewapproachtoEMlearning of PCFGs. We completely separate the process of EM learning from that of parsing, andfor theformer, weintroduce a new EM algorithm called the gra...
Taisuke Sato, Shigeru Abe, Yoshitaka Kameya, Kiyoa...
ICML
2003
IEEE
14 years 9 months ago
Optimization with EM and Expectation-Conjugate-Gradient
We show a close relationship between the Expectation - Maximization (EM) algorithm and direct optimization algorithms such as gradientbased methods for parameter learning. We iden...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
ISMIR
2005
Springer
164views Music» more  ISMIR 2005»
14 years 2 months ago
Theory and Evaluation of a Bayesian Music Structure Extractor
We introduce a new model for extracting classified structural segments, such as intro, verse, chorus, break and so forth, from recorded music. Our approach is to classify signal ...
Samer A. Abdallah, Katy Noland, Mark B. Sandler, M...
BVAI
2007
Springer
14 years 2 months ago
Classification with Positive and Negative Equivalence Constraints: Theory, Computation and Human Experiments
We tested the efficiency of category learning when participants are provided only with pairs of objects, known to belong either to the same class (Positive Equivalence Constraints ...
Rubi Hammer, Tomer Hertz, Shaul Hochstein, Daphna ...