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ICASSP
2011
IEEE
14 years 3 months ago
Subspace pursuit method for kernel-log-linear models
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Yotaro Kubo, Simon Wiesler, Ralf Schlüter, He...
ISMB
1997
15 years 1 months ago
Identifying Chimerism in Proteins Using Hidden Markov Models of Codon Usage
Protein chimerism is a phenomenon involving the combination of multiple ancestral sequences into a single, multi-domain protein through evolution. We propose a novel method for de...
Lawrence Hunter, Barry Zeeberg
EMNLP
2010
14 years 9 months ago
A Fast Fertility Hidden Markov Model for Word Alignment Using MCMC
A word in one language can be translated to zero, one, or several words in other languages. Using word fertility features has been shown to be useful in building word alignment mo...
Shaojun Zhao, Daniel Gildea
CSL
2010
Springer
14 years 12 months ago
The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management
This paper explains how Partially Observable Markov Decision Processes (POMDPs) can provide a principled mathematical framework for modelling the inherent uncertainty in spoken di...
Steve Young, Milica Gasic, Simon Keizer, Fran&cced...
AIPS
2008
15 years 2 months ago
Bounded-Parameter Partially Observable Markov Decision Processes
The POMDP is considered as a powerful model for planning under uncertainty. However, it is usually impractical to employ a POMDP with exact parameters to model precisely the real-...
Yaodong Ni, Zhi-Qiang Liu