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Ключевое слово machinelearning [180 articles]

Recent papers classified by the tag machinelearning.
  • Unifying multi-class AdaBoost algorithms with binary base learners under the margin framework
    Pattern Recogn. Lett., Vol. 28, No. 5. (April 2007), pp. 631-643.
    by Yijun Sun, Sinisa Todorovic, Jian Li
    posted to machinelearning by yosuke on 2007-12-17 07:17:46 as **
  • Multi-class AdaBoost
    by Ji Z University
    posted to machinelearning by yosuke on 2007-12-17 07:17:04 as ** along with 1 person amirsaffari
  • Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
    (2000), pp. 9-16.
    by Erin L Allwein, Robert E Schapire, Yoram Singer
    posted to machinelearning by yosuke on 2007-12-17 08:58:11 as ** along with 2 people Mohan-S sachina
  • The Random Subspace Method for Constructing Decision Forests
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 8. (1998), pp. 832-844.
    by Tin K Ho
    posted to machinelearning by yosuke on 2007-08-10 03:59:18 as ** along with 1 person thangvu
  • Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
    International Journal of Computer Vision
    by Juan Niebles, Hongcheng Wang, Li Fei-Fei
    posted to machinelearning temporalmodel by yosuke on 2008-03-06 11:26:22 as **
  • Incremental Linear Discriminant Analysis for Face Recognition
    Systems, Man, and Cybernetics, Part B, IEEE Transactions on, Vol. 38, No. 1. (2008), pp. 210-221.
    by H Zhao, PC Yuen
    posted to machinelearning by yosuke on 2008-01-24 02:38:32 as ***
  • Candid covariance-free incremental principal component analysis
    (2003)
    by J Weng, Y Zhang, W Hwang
    posted to machinelearning subspace by yosuke on 2007-12-11 09:07:47 as **
  • Unifying the error-correcting and output-code AdaBoost within the margin framework
    (2005), pp. 872-879.
    by Yijun Sun, Sinisa Todorovic, Jian Li, Dapeng Wu
    posted to machinelearning by yosuke on 2007-12-17 08:28:01 as ** along with 3 people ling sdvillal Vezhnick
  • Adaptive sparseness for supervised learning
    (2003)
    by M Figueiredo
    posted to machinelearning by yosuke on 2007-12-27 06:46:50 as ** along with 1 person winkler
  • Multi-class object recognition using boosted linear discriminant analysis combined with masking covariance matrix method Multi-class object recognition using boosted linear discriminant analysis combined with masking covariance matrix method
    Computer Vision Systems, 2006 ICVS '06. IEEE International Conference on (2006), pp. 33-33.
    by M Tanigawa, M Tanigawa
    posted to machinelearning by yosuke on 2007-12-17 07:58:18 as **
  • Feature selection, mutual information, and the classification of high-dimensional patterns
    Pattern Analysis & Applications
    by Boyan Bonev, Francisco Escolano, Miguel Cazorla
    posted to machinelearning by yosuke on 2008-02-27 02:11:21 as **
  • Bayesian Inference in Processing Experimental Data
    by Principles, Basic
    posted to machinelearning by yosuke on 2007-12-11 06:28:28 as **
  • Probabilistic bilinear models for appearance-based vision
    Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on (2003), pp. 1478-1485 vol.2.
    by DB Grimes, AP Shon, RPN Rao
    posted to machinelearning by yama_tah on 2006-01-15 23:37:19 as read
  • On the relationships between SVD, KLT and PCA
    Pattern Recognition, Vol. 14, No. 1-6. (1981), pp. 375-381.
    by Jan J Gerbrands
    posted to machinelearning by yama_tah on 2005-12-06 01:19:27 as read along with 4 people and 1 group yas dwf bamberg ashko T_lab
  • A review of principal component analysis and its applications to color technology
    Color Research & Application, Vol. 30, No. 2. (28 January 2005), pp. 84-98.
    by Di-Yuan Tzeng, Roy S Berns
    posted to machinelearning review by yama_tah on 2005-12-06 01:17:57 as read
  • KBA: kernel boundary alignment considering imbalanced data distribution
    Knowledge and Data Engineering, IEEE Transactions on, Vol. 17, No. 6. (2005), pp. 786-795.
    by G Wu, EY Chang
    posted to machinelearning by yama_tah on 2005-12-06 00:38:00 as read
  • Reducing the Dimensionality of Data with Neural Networks
    Science, Vol. 313, No. 5786. (28 July 2006), pp. 504-507.
    by GE Hinton, RR Salakhutdinov
    posted to machinelearning by yama_tah on 2006-08-05 05:46:18 as read along with 16 people and 9 groups brian pdlug ana barry garyfeng mrkrause neilh sdvillal dwf jwdietrich rgb mp4man josepe marcusfrean robincha ygarb structural_bioinformatics ReadingLab MathBio Bioinformatics Cybernetics pileWorks S-Lab Biomedical_Cybernetics AQUA-FONTIS-Study
  • A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
    Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], Vol. 50, No. 2. (2002), pp. 174-188.
    by MS Arulampalam, S Maskell, N Gordon, T Clapp
    posted to machinelearning by yama_tah on 2006-06-10 01:54:14 as read along with 9 people and 1 group jrw aufrank vema stsaft wasteland93 maxp dcastro s-fujii asterix77 ur-cls
  • Emergence of simple-cell receptive field properties by learning a sparse code for natural images.
    Nature, Vol. 381, No. 6583. (13 June 1996), pp. 607-609.
    by BA Olshausen, DJ Field
    posted to machinelearning by yama_tah on 2005-12-06 17:30:48 as read along with 2 people rmaertin bayesian
  • A global geometric framework for nonlinear dimensionality reduction.
    Science, Vol. 290, No. 5500. (22 December 2000), pp. 2319-2323.
    by JB Tenenbaum, V de Silva, JC Langford
    posted to machinelearning by yama_tah on 2005-12-06 17:29:32 as read along with 15 people and 4 groups matjes aufrank k12u yas metamerist tag mthomure sdvillal dgront voiklis dwf DavidSchulz teesid jung_dalglish mctor ur-cls T_lab metric_embeddings ColDyn
  • Nonlinear Dimensionality Reduction by Locally Linear Embedding
    Science, Vol. 290, No. 5500. (22 December 2000), pp. 2323-2326.
    by Sam T Roweis, Lawrence K Saul
    posted to machinelearning by yama_tah on 2005-12-06 17:28:21 as read along with 15 people and 4 groups matjes amargoli yaroslavvb gangli yas filippone tag sdvillal dgront walkking jguinney kenji4569 DavidSchulz mdramirez mctor tulip T_lab metric_embeddings Computer_Graphics
  • Incremental projection learning for optimal generalization.
    Neural Netw, Vol. 14, No. 1. (January 2001), pp. 53-66.
    by M Sugiyama, H Ogawa
    posted to machinelearning by yama_tah on 2005-12-06 17:17:22 as read
  • Learning When Negative Examples Abound
    (1997), pp. 146-153.
    by Miroslav Kubat, Robert Holte, Stan Matwin
    posted to machinelearning by yama_tah on 2005-12-05 23:46:02 as read
  • Separating Style and Content with Bilinear Models
    Neural Comp., Vol. 12, No. 6. (1 June 2000), pp. 1247-1283.
    by Joshua B Tenenbaum, William T Freeman
    posted to machinelearning by yama_tah on 2006-06-01 07:57:29 as read
  • Random projection in dimensionality reduction: applications to image and text data
    (2001), pp. 245-250.
    by Ella Bingham, Heikki Mannila
    posted to machinelearning by yama_tah on 2005-12-06 15:46:47 as read along with 2 people whym jelsas
  • Experiments with Random Projections for Machine Learning
    by Dmitriy Fradkin, David Madigan
    posted to machinelearning by yama_tah on 2005-12-06 15:35:36 as read
  • Classifier Technology and the Illusion of Progress
    (19 Jun 2006)
    by David J Hand
    posted to classification machinelearning by wnpx on 2006-12-07 19:48:30 as ** along with 8 people and 3 groups hardingp ecome lfriedl QFRMC sugarexpletive robincha markymaypo bross kdl QFRMC_ConsumerCredit ARTFL
  • On Supervised Learning of Bayesian Network Parameters
    by Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri
    posted to bayesian machinelearning naive supervised by wnpx on 2007-06-28 12:04:49 as **
  • Agents that Learn from Distributed Dynamic Data Sources
    (2000)
    by D Caragea, A Silvescu, V Honavar
    posted to agent distributed machinelearning by wnpx on 2006-01-30 13:54:03 as **
  • Probabilistic modeling and machine learning in structural and systems biology.
    BMC Bioinformatics, Vol. 8 Suppl 2 (2007)
    by S Kaski, J Rousu, E Ukkonen
    posted to dt machinelearning modeling new probabilistic sysbio toread by wnpx on 2007-06-28 09:47:27 as ***** along with 1 person shigepong
  • Learning from labeled and unlabeled data with label propagation
    (2002)
    by X Zhu, Z Ghahramani
    posted to machinelearning semisupervized by wnpx on 2006-01-02 16:33:06 as ** along with 2 people davidr markusd
  • A Unifying Review of Linear Gaussian Models
    (1997)
    by Sam Roweis, Zoubin Ghahramani
    posted to machinelearning unsupervised by wnpx on 2006-01-02 16:31:23 as ** along with 9 people and 2 groups noel tag ecome sbarthelme dwf bamberg sugarexpletive daniel51 assad79 metric_embeddings LTN
  • Max margin Markov networks
    (2003)
    by B Taskar, C Guestrin, D Koller
    posted to graphicalmodels machinelearning markovnets svm by wnpx on 2006-02-24 14:45:59 as ** along with 5 people and 1 group davidr buescher76 wcohen mdreid wenhan Statistical Machine Learning
  • 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 algorithm bayes machinelearning variational variationalbayes by wnpx on 2006-01-02 16:27:44 as ** along with 7 people ecome mukundn jvangael alad phitastic pythia2k jsr
  • Information Theory, Inference & Learning Algorithms
    (15 June 2002)
    by David JC Mackay
    posted to book dt inference informationtheory loan machinelearning probabilisticmodeling by wnpx on 2006-01-20 19:58:35 as *** along with 40 people and 5 groups luispedro matjes delip lop ekatsyrk quianominorleo markusd A_Olympia ansobol yaroslavvb JoSeK ingo jrw rpadams gyuli dariusb simonjudge leidner bayesian BarrosH filippone marcosmuller danielaugot zielaj daveh spirit_of_numenor sbarthelme anon_pl dwf petrijooste wowbagger nrubens chrisc rsantana fishtank rwilliamson poluxmoon robertoalamino brianmc robotact Philosophy_of_Information Blog_and_Wiki_Research AssistiveTechnology inference-group ComplexAdaptiveSystems
  • Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
    (31 August 2007)
    by L Getoor
    posted to machinelearning prm relational by wnpx on 2007-06-28 12:58:30 as ** along with 1 person paulomagalhaes
  • Rejoinder: Classifier Technology and the Illusion of Progress
    (19 Jun 2006)
    by David J Hand
    posted to classification machinelearning by wnpx on 2006-12-07 19:48:54 as ** along with 2 people and 2 groups lfriedl QFRMC kdl QFRMC_ConsumerCredit
  • Hierarchically classifying documents using very few words
    (1997), pp. 170-178.
    by Daphne Koller, Mehran Sahami
    edited by Douglas H Fisher
    posted to classification machinelearning smalltrainingset by weiwu on 2006-11-21 16:54:39 as ** along with 2 people and 1 group psylle ehohman pim
  • Text categorization for multi-page documents: a hybrid naive Bayes HMM approach
    (2001), pp. 11-20.
    by Paolo Frasconi, Giovanni Soda, Alessandro Vullo
    posted to classification machinelearning multipage by weiwu on 2006-11-21 16:52:30 as ** along with 1 group pim
  • Statistical Modeling: The Two Cultures
    Statistical Science, Vol. 16, No. 3. (2001), pp. 199-215.
    by Leo Breiman
    posted to statistics machinelearning by ulmer on 2008-05-01 23:21:55 as read along with 5 people EnlightenedDuck mdreid vqv robincha bsilverthorn
  • notes Map-Reduce for Machine Learning on Multicore
    (2006), pp. 281-288.
    by Cheng T Chu, Sang K Kim, Yi A Lin, Yuanyuan Yu, Gary R Bradski, Andrew Y Ng, Kunle Olukotun
    edited by Bernhard Schölkopf, John C Platt, Thomas Hoffman
    posted to mapreduce machinelearning by takeha-e on 2008-05-16 02:10:02 as ** along with 4 people zakk0610 coleslaw zzztimbo bhaddow
  • Interaction Is The Key To Machine Learning Applications
    by Henry Lieberman
    posted to machinelearning by suleehs on 2008-02-27 05:53:28 as ** along with 2 people kozaki brianlimyl
  • Representational Issues in Machine Learning of User Profiles
    (1996)
    by Eric Bloedorn, Inderjeet Mani, Richard T Macmillan
    posted to machinelearning by suleehs on 2008-07-15 20:00:16 as **
  • Chaos game representation for comparison of whole genomes
    BMC Bioinformatics, Vol. 7, No. 1. (2006)
    by Jijoy Joseph, Roschen Sasikumar
    posted to bioinformatics cgr machinelearning by skhadar on 2008-02-27 06:54:26 as read along with 2 people operon hpaces
  • Machine Learning and Its Applications to Biology
    PLoS Computational Biology, Vol. 3, No. 6. (1 June 2007), e116.
    by Adi L Tarca, Vincent J Carey, Xue-Wen Chen, Roberto Romero, Sorin Drăghici
    posted to bioinformatics machinelearning by skhadar on 2007-07-25 12:28:54 as ** along with 7 people and 2 groups Borelli julius cjeans asddd ciga nklee kmdaily SysbioMPI-TCells Computational_Information_Geometry
  • An Efficient k-Means Clustering Algorithm: Analysis and Implementation
    IEEE Trans. Pattern Anal. Mach. Intell., Vol. 24, No. 7. (July 2002), pp. 881-892.
    by Tapas Kanungo, David M Mount, Nathan S Netanyahu, Christine D Piatko, Ruth Silverman, Angela Y Wu
    posted to machinelearning by sethy on 2005-11-18 21:52:21 as ** along with 1 person burtonwu
  • An optimal algorithm for approximate nearest neighbor searching fixed dimensions
    J. ACM, Vol. 45, No. 6. (November 1998), pp. 891-923.
    by Sunil Arya, David M Mount, Nathan S Netanyahu, Ruth Silverman, Angela Y Wu
    posted to data-acquisition machinelearning by sethy on 2005-11-18 21:51:28 as ** along with 1 person Mbala
  • Towards adaptive classification for BCI
    Journal of Neural Engineering, Vol. 3, No. 1. (March 2006), R13.
    by Pradeep Shenoy, Matthias Krauledat, Benjamin Blankertz, Rajesh PN Rao, Klaus-Robert Müller
    posted to bci machinelearning by sebwills on 2006-05-11 13:19:50 as ** along with 1 person alklazema
  • Machine Learning
    (01 October 1997)
    by Thomas Mitchell
    posted to machinelearning ml by sb-3000 on 2005-10-26 10:38:38 as ** along with 11 people and 3 groups akastrin quianominorleo ujh ryanshaw sdvillal gatsoulis Mohan-S wkiri aklassen singhsh jliegl sims_phd_cohort_2005 digital_youth Medical Image Analysis and Visualization @ OSU
  • Bidirectional inference with the easiest-first strategy for tagging sequence data
    (2005), pp. 467-474.
    by Yoshimasa Tsuruoka, Jun'ichi Tsujii
    posted to pos ner machinelearning by satre on 2008-07-26 12:55:39 as ***
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