jsr's library 46 articles Export

	Bayesian Density Estimation and Inference Using Mixtures [My Copy] Journal of the American Statistical Association, Vol. 90, No. 430. (???? 1995), pp. 577-588. by Michael D. Escobar, Mike West posted to bayesian density_estimation dirichlet_process mcmc mixture_model by jsr on 2008-04-11 06:28:10 as along with 1 person eisdur
	Covariance kernels from Bayesian generative models [My Copy] (2000) by M. Seeger posted to bayesian gaussian_process generative_models semi_supervised by jsr on 2008-04-07 06:11:12 as
	Beyond Gaussian Processes: On the Distributions of Inﬁnite Networks [My Copy] In Proceedings of NIPS 2005 (2005) by Ricky Der, Daniel Lee posted to gaussian_process neural_networks statistics by jsr on 2008-04-06 12:34:41 as
	Exploiting generative models in discriminative classifiers [My Copy] by T. Jaakkola, D. Haussler posted to gaussian_process generative_models kernel_methods manifolds metric_learning svm by jsr on 2008-04-06 09:08:15 as along with 4 people dkulp viditjain sugarexpletive schulz
	Probabilistic Geometry [My Copy] Proceedings of the National Academy of Sciences of the United States of America, Vol. 37, No. 4. (1951), pp. 226-229. by Karl Menger posted to metric_spaces probabilistic_geometry by jsr on 2008-04-02 09:20:15 as
	Nonparametric empirical Bayes for the Dirichlet process mixture model [My Copy] Statistics and Computing, Vol. 16, No. 1. (March 2006), pp. 5-14. by Jon Mcauliffe, David Blei, Michael Jordan posted to bayesian dirichlet_process empirical_bayes mixture_model nonparametric by jsr on 2008-03-28 12:47:19 as along with 4 people bertelsen ldietz cbosuna abrentnall
	Duality Between Learning Machines: A Bridge Between Supervised and Unsupervised Learning [My Copy] Neural Computation, Vol. 6, No. 3. (1994), pp. 491-508. by Jean P. Nadal, N. Parga posted to duality perceptrons statistics by jsr on 2008-03-24 12:56:06 as along with 1 person education03
	An Introduction to Variational Methods for Graphical Models [My Copy] Machine Learning, Vol. 37, No. 2. (1999), pp. 183-233. by Michael I. Jordan, Zoubin Ghahramani, Tommi Jaakkola, Lawrence K. Saul posted to graphical_models statistical_learning statistics variational_methods by jsr on 2008-03-24 12:40:39 as along with 7 people mukundn wnpx jvangael alad phitastic pythia2k ecome
	The matrix stick-breaking process for flexible multi-task learning [My Copy] In ICML '07: Proceedings of the 24th international conference on Machine learning (2007), pp. 1063-1070. by Ya Xue, David Dunson, Lawrence Carin posted to bayesian dirichlet_process nonparametric transfer_learning by jsr on 2008-03-23 10:29:29 as
	Kernels for multi-task learning [My Copy] In Proceedings of NIPS 2004 (2004) by Charles A. Micchelli, Massimiliano Pontil posted to kernel_methods learning vector_valued_kernels by jsr on 2008-03-21 13:02:08 as
	Max-margin Classiﬁcation of Data with Absent Features [My Copy] Journal of Machine Learning Research, Vol. 9 (2008) by Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller posted to learning missing_features svm by jsr on 2008-03-21 11:25:56 as
	Metric Learning for Text Documents [My Copy] IEEE Trans. Pattern Anal. Mach. Intell., Vol. 28, No. 4. (April 2006) by Guy Lebanon posted to metric_learning nlp unsupervised_learning by jsr on 2008-03-16 12:51:46 as
	On Kernel-Target Alignment [My Copy] by Nello Cristianini, John S. Taylor, André Elisseeff posted to kernel_methods metric_learning by jsr on 2008-03-16 00:16:32 as along with 3 people and 1 group ecome atbrew teesid LTN
	Self-Organizing Homotopy Network [My Copy] In Proceedings of the 6th Annual Workshop on Self-Organizing Maps (2007) by Tetsuo Furukawa posted to fiber_bundle_learning homotopy_learning manifolds unsupervised_learning by jsr on 2008-03-15 11:28:18 as
	Metric Learning by Collapsing Classes [My Copy] In Proceedings of NIPS 2005 (2005) by Amir Globerson, Sam Roweis posted to clustering metric_learning unsupervised_learning by jsr on 2008-03-15 11:12:01 as
	Information-theoretic metric learning [My Copy] In ICML '07: Proceedings of the 24th international conference on Machine learning (2007), pp. 209-216. by Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon posted to manifolds metric_learning unsupervised_learning by jsr on 2008-03-15 11:08:23 as along with 4 people jekky sdvillal teesid jung_dalglish
	Discovering Shared Structure in Manifold Learning [My Copy] (2004) by Yoshua Bengio, Martin Monperrus posted to learning manifolds semi_supervised by jsr on 2008-03-14 05:13:46 as
	Charting a manifold [My Copy] Neural Information Processing Systems (NIPS), No. 15. (2003) by Matthew Brand posted to learning manifolds semi_supervised by jsr on 2008-03-14 05:07:33 as along with 1 person hisashim
	A Hilbert Space Embedding for Distributions [My Copy] Discovery Science (2007), pp. 40-41. by Alex Smola, Arthur Gretton, Le Song, Bernhard Schölkopf posted to hilbert_spaces kernel_methods statistical_learning by jsr on 2008-03-14 02:19:16 as
	Integration of Stochastic Models by Minimizing α-Divergence [My Copy] Neural Comput., Vol. 19, No. 10. (October 2007), pp. 2780-2796. by Shun-Ichi Amari posted to information_geometry manifolds stochastic_models by jsr on 2008-03-12 12:35:04 as
	Model Selection and the Principle of Minimum Description Length [My Copy] Journal of the American Statistical Association, Vol. 96, No. 454. (2001), pp. 746-774. by Mark H. Hansen, Bin Yu posted to information_theory mdl model_selection stochastic_compexity by jsr on 2008-03-12 11:49:15 as
	An Introduction to the MDL Principle [My Copy] by Jorma Rissanen posted to information_theory learning mdl statistics stochastic_compexity by jsr on 2008-03-12 11:43:06 as
	Warped Gaussian Processes [My Copy] (2004) by E. Snelson, C. Rasmussen, Z. Ghahramani posted to bayesian gaussian_process learning nonlinear nonparametric by jsr on 2008-03-12 08:42:42 as
	Self-Organizing Homotopy Network [My Copy] In Proceedings of the 6th Annual Workshop on Self-Organizing Maps (2007) by Tetsuo Furukawa posted to bayesian gaussian_process learning nonparametric time_series by jsr on 2008-03-12 03:22:46 as along with 18 people and 2 groups klurie jlb08r phudson penguinpan saslow ejones alchemyst JavaJoe sprite sjc bkyu38 deadman yannchev dudamma kdesmond mgallagher pick600 NervousFishdown e-JC Computerized Tomography
	Counting probability distributions: differential geometry and model selection. [My Copy] Proc Natl Acad Sci U S A, Vol. 97, No. 21. (10 October 2000), pp. 11170-11175. by I. J. Myung, V. Balasubramanian, M. A. Pitt posted to information_geometry manifolds mdl model_selection statistics by jsr on 2008-03-12 02:27:43 as along with 4 people qwermish brian yaroslavvb davidr
	Spatial Nonparametric Bayesian Models [My Copy] (2001) by S. Maceachern, A. Kottas, A. Gelfand posted to bayesian dirichlet_process gaussian_process nonparametric statistics by jsr on 2008-03-11 13:06:36 as
	A choice model with infinitely many latent features [My Copy] In ICML '06: Proceedings of the 23rd international conference on Machine learning (2006), pp. 361-368. by Dilan Görür, Frank Jäkel, Carl E. Rasmussen posted to bayesian choice_model indian_buffet_process nonparametric statistical_learning by jsr on 2008-03-10 02:38:19 as along with 2 people jonilaserson bayes
	Combinatorial Stochastic Processes [My Copy] (2002) by J. Pitman posted to statistics stochastic_processes by jsr on 2008-03-09 00:54:50 as along with 2 people markusd delip
	Hierarchical Beta Processes and the Indian Buﬀet Process [My Copy] In Proceedings of the 11th Conference on Artificial Intelligence and Statistic (2007) by Romain Thibaux, Michael I. Jordan posted to bayesian beta_process indian_buffet_process nonparametric unsupervised_learning by jsr on 2008-03-09 00:34:28 as along with 2 people markusd delip
	Stick-breaking Construction for the Indian Buffet Process [My Copy] In Proceedings of the 11th Conference on Artificial Intelligence and Statistic (2007) by Y. W. Teh, D. Gorur, Z. Ghahramani posted to bayesian indian_buffet_process nonparametric unsupervised_learning by jsr on 2008-03-08 23:13:36 as along with 1 person rpadams
	Prior Distributions for Partitions in Bayesian Nonparametrics [My Copy] (3 Jan 2008) by Lee Dicker, Shane T. Jensen posted to bayesian dirichlet_process nonparametric by jsr on 2008-03-08 12:46:00 as along with 1 person haulk
	Hierarchical Dirichlet Processes [My Copy] Journal of the American Statistical Association, Vol. 101 (December 2006) by Yee W. Teh, Michael I. Jordan, Matthew J. Beal, David M. Blei posted to bayesian clustering hierarchical_dirichlet_process latent_feature_models learning nonparametric statistical_learning by jsr on 2008-03-08 12:31:19 as along with 1 person markusd
	Pure Exploration for Multi-Armed Bandit Problems [My Copy] (19 Feb 2008) by Sebastien Bubeck, Remi Munos, Gilles Stoltz posted to bandits learning_theory online reinforcement_learning by jsr on 2008-03-08 11:56:37 as
	Metric entropy in competitive on-line prediction [My Copy] (9 Sep 2006) by Vladimir Vovk posted to learning learning_theory metric_entropy statistical_learning by jsr on 2008-03-08 11:42:11 as along with 1 person davidr
	Position Auctions [My Copy] International Journal of Industrial Organization (October 2006) by Hal Varian posted to auction_theory computational_economics game_theory mechanism_design by jsr on 2008-03-08 05:22:37 as
	On the Mathematical Foundations of Learning [My Copy] Bulletin of the American Mathematical Society, Vol. 39, No. 1. (2002), pp. 1-49. by Felipe Cucker, Steve Smale posted to learning learning_theory statistical_learning by jsr on 2008-03-08 04:42:54 as along with 1 person bsilverthorn
	Bayesian nonparametric latent feature models [My Copy] In Bayesian Statistics (2007), pp. 201-225. by Zoubin Ghahramani, T. L. Griffiths, Peter Sollich posted to bayesian indian_buffet_process latent_feature_models learning nonparametric by jsr on 2008-03-06 08:00:18 as along with 2 people bertelsen markusd
	The Use of Unlabeled Data in Predictive Modeling [My Copy] ArXiv e-prints, Vol. 710 (October 2007) by F. Liang, S. Mukherjee, M. West posted to bayesian learning manifolds semi_supervised by jsr on 2008-03-06 07:55:46 as along with 1 person bertelsen
	Infinite latent feature models and the Indian buffet process [My Copy] (2005) by T. Griffiths, Z. Ghahramani posted to bayesian indian_buffet_process learning nonparametric by jsr on 2008-03-05 11:12:10 as along with 1 person markusd
	On the Gittins Index for Multiarmed Bandits [My Copy] The Annals of Applied Probability, Vol. 2, No. 4. (1992), pp. 1024-1033. by Richard Weber posted to bandits decision_theory rl by jsr on 2008-03-05 11:06:25 as
	Evolutionarily stable strategies of random games, and the vertices of random polygons [My Copy] Annals of Applied Probability, Vol. 18, No. 1. (2008), pp. 259-287. by Sergiu Hart, Yosef Rinott, Benjamin Weiss posted to evolutionary_game_theory by jsr on 2008-03-05 10:57:16 as
	Semi-Supervised Learning on Riemannian Manifolds [My Copy] Machine Learning, Vol. 56, No. 1. (21 July 2004), pp. 209-239. by Mikhail Belkin, Partha Niyogi posted to geometry learning manifolds semi_supervised by jsr on 2008-03-05 09:39:26 as along with 1 person yanivshm
	Asymptotic Bayes Criteria for Nonparametric Response Surface Design [My Copy] Annals of Statistics, Vol. 22, No. 2. (1994), pp. 634-651. by Toby Mitchell, Jerome Sacks, Donald Ylvisaker posted to bayesian global_optimization nonparametric response_surface by jsr on 2008-03-05 09:02:44 as
	Bayesian Hierarchical Clustering [My Copy] by Katherine H. Heller posted to bayesian clustering __google__ hierarchical_clustering nonparametric by jsr on 2008-03-05 08:56:07 as along with 4 people and 1 group jrw Jaykul shilad markusd GroupLens
	A Nonparametric Bayesian Approach to Modeling Overlapping Clusters [My Copy] In Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-2007) (2007) by K. A. Heller, Z. Ghahramani posted to bayesian clustering __google__ hierarchical_clustering indian_buffet_process nonparametric by jsr on 2008-03-05 08:49:11 as along with 2 people mshafiei vlachmore
	Online Mechanisms [My Copy] In Algorithmic Game Theory by David Parkes edited by Noam Nisan, Tim Roughgarden, Eva Tardos, Vijay Vazirani posted to auction_theory computational_economics game_theory learning mechanism_design online by jsr on 2008-03-05 08:44:59 as

Note: You may cite this page as: http://www.citeulike.org/user/jsr

bayesian	18
learning	15
nonparametric	15
manifolds	9
statistics	7
unsupervised_learning	6
gaussian_process	6
statistical_learning	6
indian_buffet_process	6
dirichlet_process	5
metric_learning	5
semi_supervised	5
clustering	4
kernel_methods	4
learning_theory	3
mdl	3
game_theory	2
hierarchical_clustering	2
latent_feature_models	2
mechanism_design	2
information_geometry	2
bandits	2
svm	2
auction_theory	2
model_selection	2
online	2
computational_economics	2
generative_models	2
mixture_model	2
stochastic_compexity	2
information_theory	2
__google__	2
empirical_bayes	1
hilbert_spaces	1
global_optimization	1
density_estimation	1
transfer_learning	1
rl	1
missing_features	1
duality	1
stochastic_processes	1
metric_spaces	1
graphical_models	1
decision_theory	1
nonlinear	1
geometry	1
metric_entropy	1
hierarchical_dirichlet_process	1
stochastic_models	1
time_series	1
vector_valued_kernels	1
beta_process	1
choice_model	1
reinforcement_learning	1
mcmc	1
nlp	1
fiber_bundle_learning	1
perceptrons	1
probabilistic_geometry	1
evolutionary_game_theory	1
variational_methods	1
neural_networks	1
response_surface	1
homotopy_learning	1

jsr's library 46 articles Export

jsr's tags