Results 101 to 110 of about 511,753 (356)
Stochastic Collapsed Variational Inference for Sequential Data
, 2015 Stochastic variational inference for collapsed models has recently been successfully applied to large scale topic modelling. In this paper, we propose a stochastic collapsed variational inference algorithm in the sequential data setting. Our algorithm is
Blunsom, Phil, Wang, Pengyu
core
BMC Bioinformatics, 2014 Logos are commonly used in molecular biology to provide a compact graphical representation of the conservation pattern of a set of sequences. They render the information contained in sequence alignments or profile hidden Markov models by drawing a stack ...
T. Wheeler, J. Clements, R. Finn
semanticscholar +1 more source
Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions
Canadian Journal of Statistics, EarlyView.Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni +2 more
wiley +1 more source
Transmission Line Fault Classification Using Hidden Markov Models
IEEE Access, 2019 The maintenance of power quality in electrical power systems depends on addressing the major disturbances that may arise during generation, transmission and distribution. Many studies aim to investigate these disturbances by analyzing the behavior of the
Jean Carlos Arouche Freire +4 more
doaj +1 more source
Experiments on the Application of IOHMMs to Model Financial Returns Series [PDF]
Input/Output Hidden Markov Models (IOHMMs) are conditional hidden Markov models in which the emission (and possibly the transition) probabilities can be conditioned on an input sequence.
Réjean Ducharme +2 more
core
Understanding eye movements in face recognition using hidden Markov models.
Journal of Vision, 2014 We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data.
Tim Chuk, Antoni B. Chan, J. Hsiao
semanticscholar +1 more source
A Markov approach to credit rating migration conditional on economic states
Canadian Journal of Statistics, EarlyView.Abstract We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time‐homogeneous Markov chain. While the rating process itself possesses the Markov property only under restrictive conditions, methods ...
Michael Kalkbrener, Natalie Packham
wiley +1 more source
Ingeniare: Revista Chilena de Ingeniería, 2007 Este trabajo da a conocer el sistema de desarrollo de software para el diseño y manipulación de modelos ocultos de Markov, denominado HTK. Actualmente, la técnica de modelos ocultos de Markov es la herramienta más efectiva para implementar sistemas ...
Roberto Carrillo Aguilar
doaj
Constrained hidden Markov models for population-based haplotyping
BMC Bioinformatics, 2007 Background Haplotype Reconstruction is the problem of resolving the hidden phase information in genotype data obtained from laboratory measurements. Solving this problem is an important intermediate step in gene association studies, which seek to uncover
Toivonen Hannu +4 more
doaj +1 more source
Map representation using hidden markov models for mobile robot localization
MATEC Web of Conferences, 2018 This paper describes a map representation and localization system for a mobile robot based on Hidden Markov Models. These models are used not only to find a region where a mobile robot is, but also they find the orientation that it has.
Savage Jesus +3 more
doaj +1 more source