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bpacker's library [134 articles]

Recent papers added to bpacker's library ordered by importance.
  • Combining Labeled and Unlabeled Data with Co-training
    (1998)
    by Avrim Blum, Tom Mitchell
  • Unsupervised improvement of visual detectors using cotraining
    (2003)
    by A Levin, P Viola, Y Freund
    posted to cotraining object-detection semisupervised-learning vision by bpacker on 2007-10-14 15:40:26 as *****
  • A View of the EM Algorithm that Justifies Incremental, Sparse, and other Variants
    (1998)
    by R Neal, G Hinton
    edited by MI Jordan
  • Old and new matrix algebra useful for statistics
    (1997)
    by T Minka
  • Training Products of Experts by Minimizing Contrastive Divergence
    Neural Comp., Vol. 14, No. 8. (1 August 2002), pp. 1771-1800.
    by Geoffrey E Hinton
  • notes Regression shrinkage and selection via the lasso
    (1994)
  • Group and Topic Discovery from Relations and Text
    by Xuerui Wang, Natasha Mohanty, Andrew Mccallum
  • Topic and Role Discovery in Social Networks
    (2005)
    by Andrew Mccallum, Andres Corrada-Emmanuel, Xuerui Wang
  • Representation of Angles Embedded within Contour Stimuli in Area V2 of Macaque Monkeys
    J. Neurosci., Vol. 24, No. 13. (31 March 2004), pp. 3313-3324.
    by Minami Ito, Hidehiko Komatsu
  • Incremental learning of object detectors using a visual shape alphabet
    Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, Vol. 1 (2006), pp. 3-10.
    by A Opelt, A Pinz, A Zisserman
  • Hyperfeatures - Multilevel Local Coding for Visual Recognition
    (2006)
    by Ankur Agarwal, William Triggs
  • Visual categorization with bags of keypoints
    (2004)
    by Chris Dance, Jutta Willamowski, Lixin Fan, Cedric Bray, Gabriela Csurka
  • Discovering object categories in image collections
    (2005)
  • Sparse multinomial logistic regression: fast algorithms and generalization bounds
    Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 27, No. 6. (2005), pp. 957-968.
    posted to algorithms lasso by bpacker on 2006-03-28 01:36:37 as **** along with 1 person and 1 group davidr vision-ng
  • Tree Dependent Identically Distributed Learning
    (2005)
    by Tony Jebara, Phil Long
    posted to trees by bpacker on 2006-02-20 08:02:51 as **** along with 1 group vision-ng
  • Multiclass Object Recognition Using Sparse, Localized HMAX Features
    (2006)
    by Jim Mutch, David Lowe
  • notes Shape Matching and Object Recognition Using Low Distortion Correspondences
    (2005), pp. 26-33.
    by Alexander C Berg, Tamara L Berg, Jitendra Malik
  • Learning from Multiple sources
    (2006)
    by Koby Crammer, Michael Kearns, Jennifer Wortman
    posted to cotraining hierarchy by bpacker on 2008-02-11 19:33:57 as ***
  • A new composition theorem for learning algorithms
    (1998), pp. 583-589.
    by Nader H Bshouty
    posted to learning-theory phase-learning by bpacker on 2008-02-03 04:39:02 as ***
  • Exact Learning Composed Classes with a Small Number of Mistakes
    Learning Theory (2006), pp. 199-213.
    by Nader Bshouty, Hanna Mazzawi
    posted to learning-theory phase-learning by bpacker on 2008-02-03 04:37:25 as ***
  • Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination
    National Bureau of Economic Research Working Paper Series (July 2003), 9873.
    by Marianne Bertrand, Sendhil Mullainathan
    posted to racism social-science by bpacker on 2008-01-29 04:36:08 as ***
  • Analyzing the Effectiveness and Applicability of Co-training
    (2000), pp. 86-93.
    by Kamal Nigam, Rayid Ghani
  • Co-training from an Incremental EM Perspective
    Intelligent Data Engineering and Automated Learning – IDEAL 2004 (2004), pp. 765-773.
    by Minoo Aminian
    posted to cotraining probabilistic-models by bpacker on 2008-01-23 01:32:56 as ***
  • Learning Mixtures of Gaussians
    (1999)
    by Sanjoy Dasgupta
    posted to probabilistic-models by bpacker on 2008-01-15 02:35:37 as ***
  • Continuation methods for mixing heterogeneous sources
    (2002)
    posted to continuation-methods semisupervised-learning by bpacker on 2008-01-09 19:13:06 as ***
  • The Information Bottleneck EM algorithm
    (2003)
  • Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
    Bernoulli, Vol. 10, No. 6. (2004), pp. 989-1010.
    by Peter J Bickel, Elizaveta Levina
    posted to regularization statistics by bpacker on 2007-12-10 18:48:07 as ***
  • Regularization in statistics
    TEST, Vol. 15, No. 2. (2006), pp. 271-344.
    by Peter Bickel, Bo Li, Alexandre Tsybakov, Sara van de Geer, Bin Yu, Teófilo Valdés, Carlos Rivero, Jianqing Fan, Aad van der Vaart
    posted to boosting regularization statistics by bpacker on 2007-12-10 18:45:12 as ***
  • On the bias of information estimates
    Psychological Bulletin, Vol. 71, No. 2. (February 1969), pp. 108-109.
    by AG Carlton
    posted to statistics by bpacker on 2007-10-23 04:12:33 as ***
  • Analytical estimates of limited sampling biases in different information measures
    Network: Computation in Neural Systems, Vol. 7, No. 1. (1996), pp. 87-107.
    by Stefano Panzeri, Alessandro Treves
    posted to statistics by bpacker on 2007-10-16 00:12:23 as ***
  • Co-training and expansion: Towards bridging theory and practice
    (2004)
    by N Balcan, A Bluem, K Yang
    posted to cotraining by bpacker on 2007-10-14 15:45:42 as ***
  • An augmented PAC model for semi-supervised learning
    (2005)
    by M Balcan, A Blum
  • Exponentiated Gradient Versus Gradient Descent for Linear Predictors
    No. UCSC-CRL-94-16. (1994)
    by Jyrki Kivinen, Manfred Warmuth
  • Uncovering shared structures in multiclass classification
    (2007), pp. 17-24.
    by Yonatan Amit, Michael Fink, Nathan Srebro, Shimon Ullman
  • Online multiclass learning by interclass hypothesis sharing
    (2006), pp. 313-320.
    by Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman
    posted to boosting by bpacker on 2007-08-06 21:39:14 as *** along with 1 group vision-ng
  • Rapid object detection using a boosted cascade of simple features
    (2001)
    by P Viola, M Jones
  • Logistic Regression, AdaBoost and Bregman Distances
    (2000), pp. 158-169.
    by Michael Collins, Robert E Schapire, Yoram Singer
  • Incorporating prior knowledge into boosting
    (2002)
    by R Schapire, M Rochery, M Rahim, N Gupta
    posted to boosting priors probabilistic-models by bpacker on 2007-06-04 06:36:05 as *** along with 1 group vision-ng
  • Partially observed values
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on, Vol. 4 (2004), pp. 2825-2830 vol.4.
    by T Raiko
    posted to statistics by bpacker on 2007-01-07 17:53:41 as *** along with 1 group vision-ng
  • Unsupervised Learning by Probabilistic Latent Semantic Analysis
    Mach. Learn., Vol. 42, No. 1-2. (2001), pp. 177-196.
    by Thomas Hofmann
    posted to nlp topic by bpacker on 2006-09-21 11:37:32 as *** along with 2 people and 1 group ldietz arsyed vision-ng
  • Probabilistic abstraction hierarchies
    (2001)
    by E Segal, D Koller, D Ormoneit
    posted to hierarchy probabilistic-models by bpacker on 2006-05-09 22:46:28 as *** along with 1 group vision-ng
  • Scalable Inference in Hierarchical Generative Models
    by Thomas D Department
  • Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories
    Computer Vision and Pattern Recognition Workshop, 2004 Conference on (2004), pp. 178-178.
    by Li Fei-Fei, R Fergus, P Perona
  • Multiclass Object Recognition with Sparse, Localized Features (to appear)
    (2006)
    by Jim Mutch, David G Lowe
  • Grafting: fast, incremental feature selection by gradient descent in function space
    J. Mach. Learn. Res., Vol. 3 (2003), pp. 1333-1356.
    by Simon Perkins, Kevin Lacker, James Theiler
  • Latent dirichlet allocation
    J. Mach. Learn. Res., Vol. 3 (2003), pp. 993-1022.
    by David M Blei, Andrew Y Ng, Michael I Jordan
  • notes A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images
    Vision Research, Vol. 41, No. 18. (August 2001), pp. 2413-2423.
    by A Hyvarinen, PO Hoyer
    posted to complex-cell ica v1 vision by bpacker on 2006-03-01 19:05:15 as *** along with 1 group vision-ng
  • Learning Sparse Multiscale Image Representations
    NIPS, Vol. 15 (2003), pp. 1327-1334.
    by Phil Sallee, Bruno A Olshausen
    edited by S Becker, S Thrun, K Obermayer
    posted to sparse-coding vision by bpacker on 2006-02-23 20:51:40 as *** along with 1 group vision-ng
  • Probabilistic framework for the adaptation and comparison of image codes
    JOSA A: Optics, Image Science, and Vision, Vol. 16, No. 7. (July 1999), pp. 1587-1601.
    by Michael S Lewicki, Bruno A Olshausen
    posted to sparse-coding vision by bpacker on 2006-02-23 20:41:21 as *** along with 1 group vision-ng
  • Three learning phases for radial-basis-function networks
    Neural Networks, Vol. 14, No. 4-5. (May 2001), pp. 439-458.
    by Friedhelm Schwenker, Hans A Kestler, Gunther Palm
    posted to phase-learning sparse-coding by bpacker on 2008-02-03 04:37:44 as **
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