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SRDS
2007
IEEE
15 years 3 months ago
Using Hidden Semi-Markov Models for Effective Online Failure Prediction
A proactive handling of faults requires that the risk of upcoming failures is continuously assessed. One of the promising approaches is online failure prediction, which means that...
Felix Salfner, Miroslaw Malek
92
Voted
ISMIR
2005
Springer
205views Music» more  ISMIR 2005»
15 years 3 months ago
Learning Harmonic Relationships in Digital Audio with Dirichlet-Based Hidden Markov Models
Harmonic analysis is a standard musicological tool for understanding many pieces of Western classical music and making comparisons among them. Traditionally, this analysis is done...
J. Ashley Burgoyne, Lawrence K. Saul
ICALP
2001
Springer
15 years 1 months ago
Hidden Pattern Statistics
Abstract. We consider the sequence comparison problem, also known as “hidden pattern” problem, where one searches for a given subsequence in a text (rather than a string unders...
Philippe Flajolet, Yves Guivarc'h, Wojciech Szpank...
GCB
2000
Springer
137views Biometrics» more  GCB 2000»
15 years 1 months ago
Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models
Conventional phylogenetic tree estimation methods assume that all sites in a DNA multiple alignment have the same evolutionary history. This assumption is violated in data sets fro...
Dirk Husmeier, Frank Wright
ACL
2006
14 years 11 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone