Group: LTN - library 98 articles Export

	On Convergence Properties of the EM Algorithm for Gaussian Mixtures [My Copy] Neural Computation, Vol. 8, No. 1. (1996), pp. 129-151. by Lei Xu, Michael I. Jordan posted to mixture em by ecome to the group LTN on 2007-06-18 10:35:45 as
	Deterministic annealing for clustering, compression, classification, regression, and related optimization problems [My Copy] (1998) by K. Rose posted to em annealing by ecome to the group LTN on 2007-05-23 10:04:58 as along with 2 people geomblog anon_pl
	Mixture-model-based signal denoising [My Copy] Advances in Data Analysis and Classification, Vol. 1, No. 1. (23 March 2007), pp. 39-51. by Allou Samé, Latifa Oukhellou, Etienne Côme, Patrice Aknin posted to regression mixture em by ecome to the group LTN on 2007-04-11 10:23:39 as
	The Elements of Statistical Learning, Data Mining, Inference and Prediction [My Copy] by Trevor, Tibshirani Robert, Jerome Friedman posted to spline regression kernel by ecome to the group LTN on 2007-04-05 13:57:30 as
	Mixtures of principal component analyzers [My Copy] (1997) by M. Tipping, C. Bishop posted to pca mixture by ecome to the group LTN on 2007-04-05 13:49:16 as along with 1 person scotto36
	GTM: The Generative Topographic Mapping [My Copy] Neural Computation, Vol. 10, No. 1. (1998), pp. 215-234. by Christopher M. Bishop, Markus Svensen, Christopher K. I. Williams posted to gtm em by ecome to the group LTN on 2007-04-05 13:48:53 as along with 3 people ngiann kenji4569 DavidSchulz
	Hidden Markov Model based fault diagnosis for stamping processes [My Copy] Mechanical Systems and Signal Processing, Vol. 18, No. 2. (March 2004), pp. 391-408. by M. Ge, R. Du, Y. Xu posted to hmm diagnosis by ecome to the group LTN on 2007-04-05 08:59:08 as
	Detection and classification of abnormal process situations using multidimensional wavelet domain hidden Markov trees [My Copy] pp. 769-775. by A. Bakhtazad posted to hmm by ecome to the group LTN on 2007-04-05 08:57:20 as
	A hidden Markov model-based algorithm for fault diagnosis with partial and imperfect tests [My Copy] Systems, Man and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, Vol. 30, No. 4. (2000), pp. 463-473. by Jie Ying, T. Kirubarajan, K. R. Pattipati, A. Patterson-Hine posted to hmm by ecome to the group LTN on 2007-04-05 08:43:44 as
	The EM algorithm and Extension [My Copy] (1996) by J. Mclachlan, T. Krishnan posted to em by ecome to the group LTN on 2007-03-30 09:45:17 as
	Pattern Recognition and Machine Learning [My Copy] (2006) by C. Bishop edited by M. Jordan, J. Kleinberg, B. Sholkopf posted to no-tag by ecome to the group LTN on 2007-03-30 09:41:56 as
	Finite Mixture Models [My Copy] (2000) by Mc, D. Peel posted to mixture em by ecome to the group LTN on 2007-03-30 09:39:14 as
	EM algorithm for partially known labels [My Copy] In Data Analysis, Classification, and Related Methods, Proceedings of the 7th Conference of the International Federation of Classication Societies (IFCS-2000) (2000), pp. 161-166. by C. Ambroise, G. Govaert edited by Springer posted to partial_labels em by ecome to the group LTN on 2007-03-30 09:23:18 as
	Handling possibilistic labels in pattern classification using evidential reasoning [My Copy] Fuzzy Sets and Systems, Vol. 122, No. 3. (2001), pp. 47-62. by T. Denoeux, L. M. Zouhal posted to ds-theory by ecome to the group LTN on 2007-03-30 09:20:26 as
	Learning from an imprecise teacher: probabilistic and evidential approaches [My Copy] In ASMDA'2001, Vol. 1 (2001), pp. 100-105. by Ambroise posted to partial_labels em by ecome to the group LTN on 2007-03-30 09:18:14 as
	Logistic regression for partial labels [My Copy] In 9th International Conference IPMU'02, Vol. III (2002), pp. 1935-1941. by Y. Grandvallet posted to partial_labels logistic_regression by ecome to the group LTN on 2007-03-30 09:09:16 as
	Partially Supervised Learning by a Credal EM Approach [My Copy] : Symbolic and Quantitative Approaches to Reasoning with Uncertainty (2005), pp. 956-967. by Patrick Vannoorenberghe, Philippe Smets posted to ds-theory em by ecome to the group LTN on 2007-02-14 12:39:36 as
	Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem [My Copy] International Journal of Approximate Reasoning, Vol. 9, No. 1. (August 1993), pp. 1-35. by Philippe Smets posted to ds-theory gbt by ecome to the group LTN on 2007-02-14 12:38:41 as
	Belief functions on real numbers [My Copy] International Journal of Approximate Reasoning, Vol. 40, No. 3. (November 2005), pp. 181-223. by Philippe Smets posted to continuous ds-theory by ecome to the group LTN on 2007-02-14 12:36:56 as
	A Unified Approach to PCA, PLS, MLR and CCA [My Copy] by Magnus Borga, Tomas Landelius, Hans Knutsson posted to cca mlr pca pls by ecome to the group LTN on 2006-11-17 11:06:07 as along with 2 people statistic01 scotto36
	Probabilités analyse des données et statistique [My Copy] (1990) by G. Saporta edited by P. Techni posted to general by ecome to the group LTN on 2006-09-25 14:04:18 as
	A maximum likelihood methodology for clusterwise linear regression [My Copy] Journal of Classification, Vol. 5 (1988), pp. 249-282. by Desarbo posted to clusterwise em by ecome to the group LTN on 2006-09-20 10:24:53 as
	ICA: A flexible non-linearity and decorrelating manifold approach [My Copy] Neural Computation, Vol. 11, No. 8. (1999), pp. 1957-1983. by Everson posted to ica by ecome to the group LTN on 2006-09-18 08:52:54 as
	Blind source separation with relative newton method [My Copy] In ICA2003 (2003), pp. 897-902. by Michael Zibulevsky posted to ica newton optimization by ecome to the group LTN on 2006-08-28 12:35:22 as
	Propagation of probabilities, means and variances in Mixed graphical associations models [My Copy] Journal of the american statistical association, Vol. 87 (1992), pp. 1098-1108. by S. L. Lauritzen posted to gaussian gm linear mixed by ecome to the group LTN on 2006-08-28 09:26:07 as
	Imposing sparsity on the mixing matrix in independent component analysis [My Copy] Neurocomputing, Vol. 49 (2002), pp. 151-162. by Hyvärinen posted to ica prior sparse by ecome to the group LTN on 2006-08-28 09:12:14 as
	Independant Component Analysis [My Copy] (2001) by Aapo edited by Wiley Inter-Science posted to ica by ecome to the group LTN on 2006-08-28 09:06:01 as
	An Information-Maximization Approach to Blind Separation and Blind Deconvolution [My Copy] Neural Computation, Vol. 7, No. 6. (1995), pp. 1129-1159. by Anthony J. Bell, Terrence J. Sejnowski posted to ica by ecome to the group LTN on 2006-08-28 09:02:32 as along with 1 person jointhechink
	An introduction to graphical models [My Copy] by M. Jordan edited by U. C. Berkley posted to gm by ecome to the group LTN on 2006-08-25 11:10:01 as
	An introduction to MCMC for machine learning [My Copy] (2003) by C. Andrieu, N. de Freitas, A. Doucet, M. Jordan posted to mcmc by ecome to the group LTN on 2006-08-24 16:05:04 as along with 15 people hgfernan awg2 ansobol mshafiei pool007 jvangael sugarexpletive Vezhnick lcigler Xavier vlachmore pkammerer tresch RhysU Hans45
	Independent Factor Analysis [My Copy] Neural Computation, Vol. 11, No. 4. (1999), pp. 803-851. by Hagai Attias posted to em ica ifa by ecome to the group LTN on 2006-07-21 09:55:19 as
	Kernel ICA: An alternative formulation and its application to face recognition [My Copy] Pattern Recognition, Vol. 38, No. 10. (October 2005), pp. 1784-1787. by Jian Yang, Xiumei Gao, David Zhang, Jing-Yu Yang posted to ica kernel by ecome to the group LTN on 2006-07-21 09:42:31 as along with 1 person and 1 group garyfeng ReadingLab
	A theory of Gaussian belief functions [My Copy] International Journal of Approximate Reasoning, Vol. 14, No. 2-3. ( 1996), pp. 95-126. by Liping Liu posted to gbf by ecome to the group LTN on 2006-07-18 14:49:15 as
	Local computation of Gaussian belief functions [My Copy] International Journal of Approximate Reasoning, Vol. 22, No. 3. (December 1999), pp. 217-248. by Liping Liu posted to gbf by ecome to the group LTN on 2006-07-18 14:48:37 as
	A Unifying Review of Linear Gaussian Models [My Copy] (1997) by Sam Roweis, Zoubin Ghahramani posted to em gm by ecome to the group LTN on 2006-06-26 12:30:25 as along with 10 people and 1 group noel wnpx tag sbarthelme dwf bamberg sugarexpletive daniel51 assad79 bhaddow metric_embeddings
	Probabilistic principal component analysis [My Copy] (1997) by M. Tipping, C. Bishop posted to em pca by ecome to the group LTN on 2006-06-26 12:23:03 as along with 10 people and 2 groups pdlug davidr bpacker mad Theo walkking flavian_vasile ShaileshKumar vlachmore kohei-h vision-ng Computer_Graphics
	EM Algorithms for PCA and SPCA [My Copy] In Advances in Neural Information Processing Systems, Vol. 10 (1998) by Sam Roweis edited by Michael I. Jordan, Michael J. Kearns, Sara A. Solla posted to em pca by ecome to the group LTN on 2006-06-26 09:57:01 as along with 1 person and 4 groups jekky CMU-HCII Blog_and_Wiki_Research automatic_summarization ASR
	Learning in Graphical Models (Adaptive Computation and Machine Learning) [My Copy] (1998) by M. Jordan edited by Michael I. Jordan posted to gm by ecome to the group LTN on 2006-06-19 11:07:04 as
	Dynamic Bayesian Networks: Representation, Inference and Learning [My Copy] (2002) by K. Murphy edited by Uc posted to dbn hmm lds by ecome to the group LTN on 2006-06-19 10:47:41 as
	Un algorithme GEM pour le débruitage de signaux [My Copy] (2006) by Samé edited by Societée F. de Classification posted to em regression by ecome to the group LTN on 2006-06-19 10:18:07 as
	Régression et modèle de mélange pour le débruitage de signaux [My Copy] (2006) by Côme posted to em regression by ecome to the group LTN on 2006-06-19 10:12:58 as
	Méthodes à noyaux pour la représentation et la discrimination de signaux non-stationnaires [My Copy] (2005) by Vincent Guigue posted to lars pursuit regression by ecome to the group LTN on 2006-06-08 09:57:16 as
	Kernel Matching Pursuit [My Copy] Mach. Learn., Vol. 48, No. 1-3. (2002), pp. 165-187. by Pascal Vincent, Yoshua Bengio posted to features-selections kernel pursuit regression by ecome to the group LTN on 2006-06-08 09:50:00 as
	Least angle regression [My Copy] Ann. Statist., Vol. 32, No. 2. (2004), pp. 407-499. by Bradley Efron, Trevor Hastie, Iain Johnstone, Robert Tibshirani posted to features-selections lars pursuit regression by ecome to the group LTN on 2006-06-07 09:38:56 as along with 1 person mukundn
	A Note on the Decomposition Methods for Support Vector Regression [My Copy] by Shuo P. Liao, Hsuan T. Lin, Chih J. Lin posted to kernel regression smo by ecome to the group LTN on 2006-06-02 10:26:50 as
	A tutorial on support vector regression [My Copy] (September 2003) by Smola posted to kernel regression sv by ecome to the group LTN on 2006-05-31 16:55:25 as
	Efficient SVM Regression Training with SMO [My Copy] Machine Learning (2001) by Gary W. Flake, Steve Lawrence posted to constraints kernel quadratic regression smo by ecome to the group LTN on 2006-05-31 16:49:15 as
	An Incremental Multivariate Regression Method for Function Approximation from Noisy Data [My Copy] by Menita Carozza, Salvatore Rampone posted to constraints kernel optimization quadratic regression smo by ecome to the group LTN on 2006-05-31 16:48:27 as
	Improvements to the SMO Algorithm for SVM Regression [My Copy] IEEE-NN, Vol. 11, No. 5. (September 2000) by S. K. Shevade, S. S. Keerthi, C. Bhattacharyya, K. R. K. Murthy posted to constraints kernel optimization quadratic regression smo by ecome to the group LTN on 2006-05-31 16:47:59 as along with 1 person and 2 groups A_Olympia Philosophy_of_Information Blog_and_Wiki_Research
	Sequential minimal optimization: A fast algorithm for training support vector machines [My Copy] (1998) by J. Platt posted to constraints kernel optimization quadratic smo by ecome to the group LTN on 2006-05-31 16:47:03 as along with 4 people and 2 groups santhosh A_Olympia HlaingAungMin frcchang Philosophy_of_Information Blog_and_Wiki_Research

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kernel	24
em	20
regression	16
ds-theory	12
classifier-fusion	9
hmm	8
tbm	8
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smo	5
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gm	4
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newton	1
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sparse	1
speech	1
sv	1
svm	1

Group: LTN - library 98 articles Export

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