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NIPS
2003
13 years 6 months ago
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
Radford M. Neal, Matthew J. Beal, Sam T. Roweis
ISMB
1998
13 years 6 months ago
A Hidden Markov Model for Predicting Transmembrane Helices in Protein Sequences
A novel method to model and predict the location and orientation of alpha helices in membrane- spanning proteins is presented. It is based on a hidden Markov model (HMM) with an a...
Erik L. L. Sonnhammer, Gunnar von Heijne, Anders K...
JAIR
2006
138views more  JAIR 2006»
13 years 4 months 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
SSPR
2004
Springer
13 years 10 months ago
Tracking the Evolution of a Tennis Match Using Hidden Markov Models
The creation of a cognitive perception systems capable of inferring higher-level semantic information from low-level feature and event information for a given type of multimedia co...
Ilias Kolonias, William J. Christmas, Josef Kittle...
ICPR
2008
IEEE
13 years 11 months ago
Embedding HMM's-based models in a Euclidean space: The topological hidden Markov models
One of the major limitations of HMM-based models is the inability to cope with topology: When applied to a visible observation (VO) sequence, HMM-based techniques have difficulty ...
Djamel Bouchaffra