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Markov kernel
Results: 34

#	Item
21	POMDP-based dialogue manager adaptation to extended domains M. Gaˇsi´c, C. Breslin, M. Henderson, D. Kim, M. Szummer, B. Thomson, P. Tsiakoulis and S. Young Cambridge University Engineering Department {mg436,cb404,mh52 Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2013-08-27 04:45:47 Partially observable Markov decision process Stochastic control Literature Domain Dialogue Speech recognition Protein domain Kernel Fiction Statistics Dynamic programming
22	Non-‐Gaussian Data Assimila0on using Mixture and Kernel Piyush Tagade Hansjorg Seybold Sai Ravela Add to Reading List Source URL: www.dddas.org Language: English - Date: 2014-06-10 20:51:17 Electronic engineering Bayesian statistics Estimation theory Monte Carlo methods Markov models Ensemble Kalman filter Kalman filter Statistics Linear filters Control theory
23	Discriminative Classifiers with Generative Kernels for Noise Robust ASR M.J.F. Gales and C. Longworth Cambridge University Engineering Department Trumpington St., Cambridge CB2 1PZ, U.K. {mjfg,cl336}@eng.cam.ac.uk Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2008-06-16 09:58:25 Support vector machine Fisher kernel Speech recognition Generative model Discriminative model Hidden Markov model Statistics Statistical classification Machine learning
24	MINERVA RESEARCH FOUNDATION LECTURES Department of Mathematics Columbia University Professor Grigori Olshanski Spring 2012 Fridays 2:15-4:00 PM Add to Reading List Source URL: www.math.columbia.edu Language: English - Date: 2011-12-01 12:26:52 Point process Random matrix Markov chain Markov kernel Integral transform Plancherel measure Matrix Statistics Stochastic processes Determinantal point process
25	Bayesian Inference for Transductive Learning of Kernel Matrix Using the Tanner-Wong Data Augmentation Algorithm Zhihua Zhang [removed] Dit-Yan Yeung Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:20:03 Expectation–maximization algorithm Missing data Matrix Conjugate prior Support vector machine Markov chain Statistics Statistical classification Estimation theory
26	Gaussian Process Classification for Segmenting and Annotating Sequences Yasemin Altun Department of Computer Science, Brown University, Providence, RI[removed]USA Thomas Hofmann Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:19:16 Statistical classification Support vector machine Normal distribution Kernel trick Hidden Markov model Gaussian process Conditional random field Statistics Machine learning Markov models
27	Augmented Statistical Models for Classifying Sequence Data Martin Layton Corpus Christi College University of Cambridge Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2008-01-16 04:35:17 Statistical classification Machine learning Markov models Hidden Markov model Fisher kernel Generative model Expectation–maximization algorithm Mixture model Maximum likelihood Statistics Estimation theory Statistical models
28	KERNELIZED LOG LINEAR MODELS FOR CONTINUOUS SPEECH RECOGNITION Shi-Xiong Zhang and M.J.F. Gales Department of Engineering, University of Cambridge, Cambridge, UK {sxz20, mjfg}@eng.cam.ac.uk ABSTRACT Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2013-03-27 12:44:34 Computational linguistics Support vector machine Kernel Hidden Markov model Speech recognition Pattern recognition Statistics Statistical classification Machine learning
29	CONVERGENCE RATES FOR DIFFUSIONS ON CONTINUOUS-TIME LATTICES ´ CLAUDIO ALBANESE AND ALEKSANDAR MIJATOVIC IMPERIAL COLLEGE LONDON Abstract. In this paper we introduce a discretization scheme based on a continuous-time Add to Reading List Source URL: www.albanese.co.uk Language: English - Date: 2014-03-17 15:14:16 Markov processes Digital signal processing Fourier analysis Markov chain Continuous-time Markov process Dirac delta function Stochastic process Kernel Discrete Fourier transform Mathematical analysis Statistics Mathematics
30	in Advances in Neural Information Processing Systems 15 S. Becker, S. Thrun and K. Obermayer (eds.), MIT Press[removed]Exponential Family PCA for Belief Compression in POMDPs Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2003-06-04 12:36:51 Principal component analysis Nonlinear dimensionality reduction Dimension reduction Non-negative matrix factorization Kullback–Leibler divergence Markov decision process Singular value decomposition Divergence Kernel principal component analysis Statistics Multivariate statistics Partially observable Markov decision process

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