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UAI
1998
13 years 8 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
ICML
2010
IEEE
13 years 8 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
TIFS
2010
123views more  TIFS 2010»
13 years 5 months ago
A new framework for adaptive multimodal biometrics management
This paper presents a new evolutionary approach for adaptive combination of multiple biometrics to ensure the optimal performance for the desired level of security. The adaptive c...
Ajay Kumar, Vivek Kanhangad, David Zhang
ACL
2009
13 years 5 months ago
Dependency Based Chinese Sentence Realization
This paper describes log-linear models for a general-purpose sentence realizer based on dependency structures. Unlike traditional realizers using grammar rules, our method realize...
Wei He, Haifeng Wang, Yuqing Guo, Ting Liu
COLING
2010
13 years 2 months ago
A Discriminative Latent Variable-Based "DE" Classifier for Chinese-English SMT
Syntactic reordering on the source-side is an effective way of handling word order differences. The (DE) construction is a flexible and ubiquitous syntactic structure in Chinese w...
Jinhua Du, Andy Way