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Estimation theory / Machine learning / Bioinformatics / Hidden Markov model / Markov chain / Mixture model / Baum–Welch algorithm / Expectation–maximization algorithm / Speech recognition / Statistics / Markov models / Probability and statistics


Sparseness Achievement in Hidden Markov Models Manuele Bicego∗ DEIR - University of Sassari via Torre Tonda, [removed]Sassari - Italy
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Document Date: 2011-10-29 17:56:25

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File Size: 280,38 KB

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City

San Mateo / Turin / Ostendorf / Verona / New York / /

Company

Computer Vision Systems / Neural Information Processing Systems / MIT Press / John Wiley & Sons / /

Country

Italy / United Kingdom / /

Currency

USD / /

Facility

University of Verona Strada Le Grazie / University of Sassari / /

IndustryTerm

model search / probabilistic sequential tool / continuous online gesture recognition / successive state splitting algorithm / closed formed solution / based online handwriting recognition / learning algorithm / /

Organization

University of Verona Strada Le Grazie / MIT / Pattern Analysis Machine Intelligence / University of Sassari / Pattern Analysis and Machine Intelligence / /

Person

M. Bicego / V / Morgan Kaufmann / /

Position

model / i.e / high representative / Markov Model for sequence analysis / /

ProgrammingLanguage

Standard ML / /

ProvinceOrState

New York / California / /

Technology

speech recognition / modified Expectation Maximization algorithm / gesture recognition / modified EM algorithm / successive state splitting algorithm / /

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