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Expectationmaximization algorithm
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1	Spectral learning of linear dynamics from generalised-linear observations with application to neural population data Lars Buesing∗ , Jakob H. Macke∗,† , Maneesh Sahani Gatsby Computational Neuroscience Unit Add to Reading List Source URL: www.mackelab.org Language: English - Date: 2016-08-04 15:02:44 Statistics Statistical theory Estimation theory Actuarial science Expectationmaximization algorithm Missing data Maximum likelihood estimation Variational Bayesian methods Linear regression Normal distribution Covariance Regression analysis
2	Interactive HMM construction based on interesting sequences Szymon Jaroszewicz National Institute of Telecommunications Warsaw, Poland Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2009-11-06 11:55:58 Markov models Machine learning Probability Statistics Bioinformatics Computational linguistics Hidden Markov model Markov chain BaumWelch algorithm Speech recognition Expectationmaximization algorithm Association rule learning
3	That was fast! Speeding up NN search of high dimensional distributions. Emanuele Coviello University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093 Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:02:39 Statistics Geometry Statistical distance Information Statistical theory Information theory Bregman divergence Search algorithms KullbackLeibler divergence Variational Bayesian methods Expectationmaximization algorithm Divergence
4	EFFICIENT INITIALIZATION OF MIXTURES OF EXPERTS FOR HUMAN POSE ESTIMATION Huazhong Ning, Yuxiao Hu, Thomas Huang ECE Department, U. of Illinois at Urbana-Champaign, Urbana, IL 61801. {hning2,hu3, huang}@ifp.uiuc.edu ABS Add to Reading List Source URL: www.ifp.illinois.edu Language: English - Date: 2008-01-22 16:26:01 Statistics Applied mathematics Machine learning Learning Expectationmaximization algorithm Pattern recognition Regression analysis Mixture model Artificial neural network Perceptron
5	Scalable Training of Mixture Models via Coresets Dan Feldman MIT Matthew Faulkner Add to Reading List Source URL: eew.caltech.edu Language: English - Date: 2012-05-15 11:47:37 Statistics Probability Maximum likelihood estimation Probability distributions Bayesian statistics Expectationmaximization algorithm Mixture model Normal distribution K-means clustering Likelihood function Data stream clustering Gamma distribution
6	C:/Users/Utente/Desktop/PhD/CAL_tex/ISMIR2010_DTM/ISMIR2010_DTM.dvi Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:02:39 Statistics Estimation theory Physics Mechanical engineering Cluster analysis Machine learning Mixture model Expectationmaximization algorithm Maximum likelihood estimation Work
7	2013 IEEE International Conference on Computer Vision Cosegmentation and Cosketch by Unsupervised Learning Jifeng Dai1,2 , Ying Nian Wu2 , Jie Zhou1 , and Song-Chun Zhu2 1 Department of Automation, Tsinghua University, Add to Reading List Source URL: www.stat.ucla.edu Language: English - Date: 2014-04-20 03:06:17 Image processing Statistics Artificial intelligence Image segmentation Machine learning Mixture model Template matching Market segmentation Expectationmaximization algorithm
8	Inferring OD-Pairs and Utility-Based Travel Preferences of Shared Mobility System Users in a Multi-Modal Environment Anshuman Anjani Kumar1 , Jee Eun Kang1 , Changhyun Kwon2 , and Alexander Nikolaev1 1 Department Add to Reading List Source URL: www.chkwon.net Language: English - Date: 2016-08-04 11:55:32 Statistics Statistical models Transportation planning Estimation theory Mode choice Traveler Logit Bayesian inference Expectationmaximization algorithm Bayesian network Mode Random sample consensus
9	SIGNAL PROCESSING LETTERS 1 The Random Walk Model Kalman Filter in Multichannel Active Noise Control Add to Reading List Source URL: www.inesc-id.pt Language: English - Date: 2015-09-02 03:38:15 Digital signal processing Telecommunications engineering Signal processing Control theory Time series analysis Estimation theory Robot control Recursive least squares filter Adaptive filter Kalman filter Expectationmaximization algorithm Algorithm
10	Journal of Artificial Intelligence Research–774 Submitted 03/10; publishedIntrusion Detection using Continuous Time Bayesian Networks Jing Xu Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2011-01-19 19:25:19 Statistics Estimation theory Control theory Mathematical analysis Markov models Graphical models Bayesian network Maximum likelihood estimation Expectationmaximization algorithm Markov chain Discretization State-space representation

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