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jsr library [46 articles]

最近 jsr さんのライブラリ .
  • notes Bayesian Density Estimation and Inference Using Mixtures
    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 read
  • Covariance kernels from Bayesian generative models
    (2000)
    by M Seeger
    posted to bayesian gaussian_process generative_models semi_supervised by jsr on 2008-04-07 06:11:12 as read
  • Beyond Gaussian Processes: On the Distributions of Infinite Networks
    (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
    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 read along with 5 people dkulp viditjain sugarexpletive amirsaffari schulz
  • Probabilistic Geometry
    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 read
  • Nonparametric empirical Bayes for the Dirichlet process mixture model
    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 read along with 2 people and 1 group ldietz cbosuna Skill-Inference
  • Duality Between Learning Machines: A Bridge Between Supervised and Unsupervised Learning
    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 ***
  • An Introduction to Variational Methods for Graphical Models
    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 6 people mukundn wnpx jvangael alad phitastic pythia2k
  • The matrix stick-breaking process for flexible multi-task 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 read
  • Kernels for multi-task learning
    (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
    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
    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
    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
    (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
    (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
    (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 3 people sdvillal teesid jung_dalglish
  • Discovering Shared Structure in Manifold Learning
    (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
    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
    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
    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
    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
    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
    (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 read
  • Self-Organizing Homotopy Network
    (2007)
    by Tetsuo Furukawa
    posted to bayesian gaussian_process learning nonparametric time_series by jsr on 2008-03-12 03:22:46 as read along with 9 people kdesmond mgallagher sprite sjc gigijms bkyu38 deadman yannchev dudamma
  • Counting probability distributions: differential geometry and model selection.
    Proc Natl Acad Sci U S A, Vol. 97, No. 21. (10 October 2000), pp. 11170-11175.
    by IJ Myung, V Balasubramanian, MA Pitt
    posted to information_geometry manifolds mdl model_selection statistics by jsr on 2008-03-12 02:27:43 as read along with 3 people brian yaroslavvb davidr
  • Spatial Nonparametric Bayesian Models
    (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
    (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 1 person bayes
  • Combinatorial Stochastic Processes
    (2002)
    by J Pitman
    posted to statistics stochastic_processes by jsr on 2008-03-09 00:54:50 as ** along with 1 person markusd
  • Hierarchical Beta Processes and the Indian Buffet Process
    (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 read along with 1 person markusd
  • Stick-breaking Construction for the Indian Buffet Process
    (2007)
    by YW Teh, D Gorur, Z Ghahramani
    posted to bayesian indian_buffet_process nonparametric unsupervised_learning by jsr on 2008-03-08 23:13:36 as read along with 1 person rpadams
  • Prior Distributions for Partitions in Bayesian Nonparametrics
    (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 ***
  • Hierarchical Dirichlet Processes
    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
    (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
    (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
    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 read
  • On the Mathematical Foundations of Learning
    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 read along with 1 person bsilverthorn
  • Bayesian nonparametric latent feature models
    (2007), pp. 201-225.
    by Zoubin Ghahramani, TL Griffiths, Peter Sollich
    posted to bayesian indian_buffet_process latent_feature_models learning nonparametric by jsr on 2008-03-06 08:00:18 as read along with 1 person markusd
  • The Use of Unlabeled Data in Predictive Modeling
    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 ***
  • notes Infinite latent feature models and the Indian buffet process
    (2005)
    by T Griffiths, Z Ghahramani
    posted to bayesian indian_buffet_process learning nonparametric by jsr on 2008-03-05 11:12:10 as read along with 1 person markusd
  • notes On the Gittins Index for Multiarmed Bandits
    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 **
  • notes Evolutionarily stable strategies of random games, and the vertices of random polygons
    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
    Mach. Learn., Vol. 56, No. 1-3. (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 *****
  • Asymptotic Bayes Criteria for Nonparametric Response Surface Design
    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
    by Katherine H Heller
    posted to bayesian clustering __google__ hierarchical_clustering nonparametric by jsr on 2008-03-05 08:56:07 as read along with 4 people and 1 group jrw Jaykul shilad markusd GroupLens
  • A Nonparametric Bayesian Approach to Modeling Overlapping Clusters
    (2007)
    by KA Heller, Z Ghahramani
    posted to bayesian clustering __google__ hierarchical_clustering indian_buffet_process nonparametric by jsr on 2008-03-05 08:49:11 as read along with 2 people mshafiei vlachmore
  • Online Mechanisms
    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 read
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