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CORR
2010
Springer
136views Education» more  CORR 2010»
13 years 5 months ago
The Highest Expected Reward Decoding for HMMs with Application to Recombination Detection
Abstract. Hidden Markov models are traditionally decoded by the Viterbi algorithm which finds the highest probability state path in the model. In recent years, several limitations ...
Michal Nánási, Tomás Vinar, B...
CSL
2000
Springer
13 years 7 months ago
Efficient speech recognition using subvector quantization and discrete-mixture HMMS
This paper introduces a new form of observation distributions for hidden Markov models (HMMs), combining subvector quantization and mixtures of discrete distrib utions. Despite w...
Vassilios Digalakis, S. Tsakalidis, Costas Harizak...
JMLR
2010
112views more  JMLR 2010»
13 years 2 months ago
Reduced-Rank Hidden Markov Models
Hsu et al. (2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their assumptions and prove a tighte...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
BMCBI
2010
123views more  BMCBI 2010»
13 years 7 months ago
Decoding HMMs using the k best paths: algorithms and applications
Background: Traditional algorithms for hidden Markov model decoding seek to maximize either the probability of a state path or the number of positions of a sequence assigned to th...
Daniel G. Brown 0001, Daniil Golod
SIGMOD
2009
ACM
134views Database» more  SIGMOD 2009»
14 years 7 months ago
Keyword query cleaning using hidden Markov models
In this paper, we consider the problem of keyword query cleaning for structured databases from a probabilistic approach. Keyword query cleaning consists of rewriting the user quer...
Ken Q. Pu