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122
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ACL
1994
15 years 4 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick
130
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BMCBI
2007
142views more  BMCBI 2007»
15 years 2 months ago
Improving model construction of profile HMMs for remote homology detection through structural alignment
Background: Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addre...
Juliana S. Bernardes, Alberto M. R. Dávila,...
166
Voted
BMCBI
2011
14 years 6 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
120
Voted
ICIAP
2001
Springer
16 years 2 months ago
Bayesian Face Recognition with Deformable Image Models
We propose a novel representation for characterizing image differences using a deformable technique for obtaining pixel-wise correspondences. This representation, which is based o...
Baback Moghaddam, Chahab Nastar, Alex Pentland
122
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AMAST
2000
Springer
15 years 7 months ago
Meta Languages in Algebraic Compilers
Abstract. Algebraic compilers provide a powerful and convenient mechanism for specifying language translators. With each source language operation one associates a computation for ...
Eric Van Wyk