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ESWA
2007
117views more  ESWA 2007»
9 years 22 hour ago
An HMM for detecting spam mail
Hidden Markov Models, or HMMs for short, have been recently used in Bioinformatics for the classification of DNA or protein chains, giving rise to what is known as Profile Hidde...
José Gordillo, Eduardo Conde
JAIR
2006
138views more  JAIR 2006»
9 years 1 days ago
Logical Hidden Markov Models
Logical hidden Markov models (LOHMMs) upgrade traditional hidden Markov models to deal with sequences of structured symbols in the form of logical atoms, rather than flat characte...
Kristian Kersting, Luc De Raedt, Tapani Raiko
IJFCS
2008
49views more  IJFCS 2008»
9 years 2 days ago
A Markovian Approach for the Analysis of the gene Structure
Hidden Markov models (HMMs) are effective tools to detect series of statistically homogeneous structures, but they are not well suited to analyse complex structures. Numerous meth...
Christelle Melo de Lima, Laurent Gueguen, Christia...
BMCBI
2008
103views more  BMCBI 2008»
9 years 5 days ago
Parameter estimation for robust HMM analysis of ChIP-chip data
Background: Tiling arrays are an important tool for the study of transcriptional activity, proteinDNA interactions and chromatin structure on a genome-wide scale at high resolutio...
Peter Humburg, David Bulger, Glenn Stone
ICPR
2010
IEEE
9 years 7 days ago
High-Level Feature Extraction Using SIFT GMMs and Audio Models
—We propose a statistical framework for high-level feature extraction that uses SIFT Gaussian mixture models (GMMs) and audio models. SIFT features were extracted from all the im...
Nakamasa Inoue, Tatsuhiko Saito, Koichi Shinoda, S...
ICASSP
2010
IEEE
9 years 8 days ago
Framework for cross-language automatic phonetic segmentation
Annotation of large multilingual corpora remains a challenge to the data-driven approach to speech research, especially for under-resourced languages. This paper presents crosslan...
Udochukwu Kalu Ogbureke, Julie Carson-Berndsen
ICML
2010
IEEE
9 years 1 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
NIPS
1992
9 years 1 months ago
Hidden Markov Model} Induction by Bayesian Model Merging
This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
Andreas Stolcke, Stephen M. Omohundro
NIPS
1994
9 years 1 months ago
An Input Output HMM Architecture
We introduce a recurrent architecture having a modular structure and we formulate a training procedure based on the EM algorithm. The resulting model has similarities to hidden Ma...
Yoshua Bengio, Paolo Frasconi
NAACL
1994
9 years 1 months ago
Statistical Language Processing Using Hidden Understanding Models
This paper introduces a class of statistical mechanisms, called hidden understanding models, for natural language processing. Much of the framework for hidden understanding models...
Scott Miller, Richard M. Schwartz, Robert J. Bobro...
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