Hidden Markov models - PDFSEARCH.IO - Document Search Engine

Hidden Markov models
Results: 740

#	Item
161	Multi-target pitch tracking of vibrato sources in noise using the GM-PHD filter Dan Stowell and Mark D. Plumbley Centre for Digital Music, Queen Mary University of London, UK Add to Reading List Source URL: c4dm.eecs.qmul.ac.uk Language: English - Date: 2012-07-12 06:18:41 Signal processing Filter theory Markov models Bioinformatics Hidden Markov model Electronic filter Filter Synthesizer Vibrato Music Electronic engineering Electronics
162	To Appear: Body Sensor Networks Workshop, Boston MA, AprilMulti-sensor Data Fusion Using the Influence Model Wen Dong and Alex Pentland E15-383, 20 Ames Street The MIT Media Laboratory Add to Reading List Source URL: vismod.media.mit.edu Language: English - Date: 2006-01-25 11:22:24 Markov processes Markov chain Hidden Markov model Expectation–maximization algorithm Stochastic process Matrix Mixture model Normal distribution Sensor Statistics Markov models Statistical models
163	Bayesian MAP estimation of piecewise arcs in tempo time-series Dan Stowell1 and Elaine Chew1 Centre for Digital Music, Queen Mary, University of London Add to Reading List Source URL: c4dm.eecs.qmul.ac.uk Language: English - Date: 2012-07-12 06:23:44 Probability and statistics Statistical inference Prior probability Hidden Markov model Viterbi algorithm A priori Arc Estimation theory Bayesian statistics Statistics Markov models
164	Probabilistic Movement Modeling for Intention Inference in Human-Robot Interaction Zhikun Wang1,2 , Katharina Mülling1,2 , Marc Peter Deisenroth2 , Heni Ben Amor2 , David Vogt3 , Bernhard Schölkopf1 , and Jan Peters1,2 Add to Reading List Source URL: www.is.tuebingen.mpg.de Language: English - Date: 2013-02-21 04:12:48 Markov models Expectation–maximization algorithm Missing data Particle filter Hidden Markov model Kalman filter Normal distribution Maximum likelihood Inference Statistics Estimation theory Robot control
165	R Foundations and Trends in Machine Learning Vol. 4, No–373 c 2012 C. Sutton and A. McCallum Add to Reading List Source URL: homepages.inf.ed.ac.uk Language: English - Date: 2012-08-27 13:34:18 Probability Machine learning Statistical models Bayesian statistics Theoretical computer science Conditional random field Hidden Markov model Discriminative model Generative model Statistics Probability and statistics Graphical models
166	Non-negative Hidden Markov Modeling of Audio with Application to Source Separation Gautham J. Mysore1⋆ , Paris Smaragdis2 , and Bhiksha Raj3 1 Center for Computer Research in Music and Acoustics, Stanford University, Add to Reading List Source URL: mlsp.cs.cmu.edu Language: English - Date: 2010-09-29 23:42:24 Statistical models Qt Widget toolkits Hidden Markov model Markov chain Speech recognition Mixture model Non-negative matrix factorization Graphical model Software Statistics Markov models
167	Probabilistic Modeling of Human Movements for Intention Inference Zhikun Wang1,2 , Marc Peter Deisenroth2 , Heni Ben Amor2 , David Vogt3 , Bernhard Schölkopf1 , Jan Peters1,2 1 MPI for Intelligent Systems, Spemannstr. 3 Add to Reading List Source URL: www.is.tuebingen.mpg.de Language: English - Date: 2012-06-11 09:24:01 Linear filters Markov models Bayesian statistics Kalman filter Expectation–maximization algorithm Hidden Markov model Gaussian process Gaussian function Normal distribution Statistics Estimation theory Robot control
168	Using Influence Model to Detect Group Interactions Add to Reading List Source URL: vismod.media.mit.edu Language: English - Date: 2005-07-25 11:44:24 Markov models Markov chain Hidden Markov model
169	A Comparison of Latent Variable Models For Conversation Analysis Sourish Chaudhuri and Bhiksha Raj Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA. Add to Reading List Source URL: www.sigdial.org Language: English - Date: 2011-05-30 23:45:59 Markov models Oral communication Conversation analysis Discourse analysis Speech recognition Hidden Markov model Conversation N-gram Language model Linguistics Computational linguistics Science
170	Characterizing Individual Communication Patterns R. Dean Malmgren1,2 , Jake M. Hofman1 , Luís A. N. Amaral2 , and Duncan J. Watts1 Yahoo! Research 111 W 40th St, 17th Floor New York, NY 10018, USA 1 Add to Reading List Source URL: www.jakehofman.com Language: English - Date: 2014-02-26 15:40:26 Data analysis Machine learning Bioinformatics Markov chain Hidden Markov model Parameter Data mining Poisson process Expectation–maximization algorithm Statistics Markov models Markov processes