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markusd's library [201 articles]

最近录入 markusd's 文献库.
  • Infinite Hidden Relational Models
    (2006)
    by Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel
    posted to machine-learning by markusd on 2008-05-13 16:12:38 as ** along with 1 person ldietz
  • Structured priors for structure learning
    (2006)
    by V Mansinghka, C Kemp, J Tenenbaum, T Griffiths
    posted to machine-learning by markusd on 2008-05-13 16:12:01 as ** along with 1 person ldietz
  • Hidden conditional random fields for phone classification
    (2005)
    by Asela Gunawardana, Milind Mahajan, Alex Acero, John C Platt
    posted to machine-learning hcrf discriminative crf by markusd on 2008-05-13 14:56:16 as **
  • Training algorithms for hidden conditional random fields
    (2006)
    by Milind Mahajan, Asela Gunawardana, Alex Acero
    posted to machine-learning hcrf discriminative crf by markusd on 2008-05-13 14:54:42 as **
  • Regularization, Adaptation, and Non-Independent Features Improve Hidden Conditional Random Fields for Phone Classification
    (2007)
    by Yun-Hsuan Sung, Constantinos Boulis, Christopher Manning, Dan Jurafsky
    posted to morphology-project hcrf discriminative crf by markusd on 2008-05-13 14:48:16 as **
  • Morphology Induction from Limited Noisy Data Using Approximate String Matching
    (June 2006), pp. 60-68.
    by Burcu K Ayan, David Doermann, Amy Weinberg
    posted to morphology-project by markusd on 2008-05-07 19:43:29 as ** along with 1 person whym
  • Learning Probabilistic Paradigms for Morphology in a Latent Class Model
    (June 2006), pp. 69-78.
    by Erwin Chan
    posted to morphology-project by markusd on 2008-05-07 19:42:52 as ** along with 1 person whym
  • Factor graphs and the sum-product algorithm
    Information Theory, IEEE Transactions on, Vol. 47, No. 2. (2001), pp. 498-519.
    by FR Kschischang, BJ Frey, HA Loeliger
    posted to morphology-project machine-learning by markusd on 2008-05-07 19:41:44 as ** along with 14 people nojhan dlmace yaroslavvb metamerist pcarbo marcosmuller rwm101 chenjinhui rsantana ElQuijote42 zeppe john_ardelius daniel51 delip
  • Inside-Outside Probability Computation for Belief Propagation
    (2007)
    by Taisuke Sato
    posted to machine-learning belief-propagation by markusd on 2008-05-07 19:41:33 as ** along with 1 person yaroslavvb
  • An introduction to factor graphs
    Signal Processing Magazine, IEEE, Vol. 21, No. 1. (2004), pp. 28-41.
    by HA Loeliger
    posted to graphical-models graph by markusd on 2008-05-07 19:38:25 as ** along with 1 person yaroslavvb
  • Walk-Sums and Belief Propagation in Gaussian Graphical Models
    Journal of Machine Learning Research, Vol. 7 (October 2006)
    by Dmitry Malioutov, Jason Johnson, Alan Willsky
    posted to machine-learning belief-propagation by markusd on 2008-05-07 19:38:16 as ** along with 2 people yaroslavvb daniel51
  • Understanding the Subprime Mortgage Crisis
    Social Science Research Network Working Paper Series (29 February 2008)
    by Yuliya Demyanyk, Otto VAN Hemert
    posted to misc by markusd on 2008-05-07 19:37:50 as ** along with 1 person pdlug
  • The Infinite Hidden Markov Model
    (2002)
    by MJ Beal, Z Ghahramani, CE Rasmussen
    posted to machine-learning by markusd on 2008-05-07 19:37:36 as ** along with 1 person nojhan
  • The Infinite Markov Model
    (2008)
    by Daichi Mochihashi, Eiichiro Sumita
    edited by JC Platt, D Koller, Y Singer, S Roweis
    posted to machine-learning by markusd on 2008-05-07 19:37:13 as ** along with 1 person whym
  • Introduction: A Typological Approach to Algorithmic Morphology
    (November 2007)
    by T Mayer, B Wälchli
    posted to morphology-project by markusd on 2008-05-07 19:36:59 as ** along with 1 person whym
  • Graph Walks and Graphical Models
    (2007)
    by William Cohen
    posted to graph by markusd on 2008-05-07 19:35:58 as ** along with 1 person yaroslavvb
  • Graph Theory
    by Frank Harary
    posted to graphs by markusd on 2008-05-07 19:34:53 as ** along with 5 people and 1 group yaroslavvb nkorf wnpx bigbossman Repton Semantic-Social-Networks
  • Foundations of Statistical Natural Language Processing
    (18 June 1999)
    by Christopher D Manning, Hinrich Schtze
    posted to nlp by markusd on 2008-05-07 19:34:28 as ** along with 29 people and 7 groups quianominorleo jliegl yaroslavvb creswick phlow Enro korakot pdlug fmatthes arthit jelsas bkhl tijl nkorf grzegorz leidner vera46 caomo bigbossman phoenix makimoto whym florianleitner takifugu matwendt suizan pprett bemike spinaltap526 Philosophy_of_Information Blog_and_Wiki_Research automatic_summarization STP Pattern-Analysis Semantic-Social-Networks AI
  • Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods
    by AFM Smith, GO Roberts
    posted to machine-learning gibbs by markusd on 2008-05-07 19:34:04 as ** along with 2 people pcarbo icosma
  • PCA versus LDA
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 2. (2001), pp. 228-233.
    by Aleix M Martinez, Avinash C Kak
    posted to machine-learning by markusd on 2008-05-07 17:01:11 as **
  • PCA versus LDA
    IEEE Trans. Pattern Anal. Mach. Intell., Vol. 23, No. 2. (February 2001), pp. 228-233.
    by Aleix M Mart∈ez, Avinash C Kak
    posted to machine-learning by markusd on 2008-05-07 16:59:54 as ** along with 1 person and 1 group ldietz Skill-Inference
  • Machine Learning
    (01 March 1997)
    by Tom M Mitchell
    posted to machine-learning by markusd on 2008-05-07 16:53:46 as ** along with 20 people and 3 groups pdlug yaroslavvb jelsas kmregan carueda jounih buescher76 mthomure hansjoergmueller brunomelo cerkut jvangael ajylha girschick zchen teesid dquercia robotact jdu sfeige AI RiSE contact-id
  • Exponential Priors for Maximum Entropy Models
    (2003)
    by J Goodman
    posted to machine-learning by markusd on 2008-05-07 16:51:53 as ** along with 1 person whym
  • The information bottleneck method
    (1999), pp. 368-377.
    by N Tishby, F Pereira, W Bialek
    posted to machine-learning by markusd on 2008-05-07 16:51:47 as ** along with 12 people and 4 groups i-stevenson yaroslavvb geomblog gangli yiqingtu thsant mhay ajbattle sdvillal anon_pl 223rem vlachmore tulip kdl DataMining vision-ng
  • Pattern Recognition and Machine Learning (Information Science and Statistics)
    (28 August 2006)
    by Christopher M Bishop
    posted to sum-product machine-learning by markusd on 2008-05-07 16:51:39 as ** along with 18 people and 5 groups eddymier yaroslavvb sdvillal nojhan gkvas paulinus ajylha helsley hawkes zeppe poluxmoon librain kohei-h brianmc napvasconcelos teesid robotact Hoertnagl EvolutionaryComputation Metaheuristics Optimization contact-id MuSAMA
  • Information Theory, Inference & Learning Algorithms
    (15 June 2002)
    by David JC Mackay
    posted to machine-learning information-theory by markusd on 2008-05-07 16:51:28 as ** along with 35 people and 5 groups A_Olympia ansobol yaroslavvb JoSeK ingo jrw rpadams gyuli dariusb simonjudge leidner bayesian BarrosH wnpx filippone marcosmuller danielaugot zielaj daveh spirit_of_numenor sbarthelme anon_pl dwf lop petrijooste wowbagger nrubens chrisc rsantana fishtank rwilliamson poluxmoon robertoalamino brianmc robotact Philosophy_of_Information Blog_and_Wiki_Research AssistiveTechnology inference-group ComplexAdaptiveSystems
  • Discovering Significant Patterns
    Machine Learning
    by Geoffrey Webb
    posted to machine-learning by markusd on 2008-05-07 16:51:15 as ** along with 4 people briordan zoop katja msampson
  • Annealing stochastic approximation Monte Carlo algorithm for neural network training
    Machine Learning, Vol. 68, No. 3. (23 October 2007), pp. 201-233.
    by Faming Liang
    posted to machine-learning by markusd on 2008-05-07 16:51:05 as ** along with 1 person pcarbo
  • Discrete Mathematics for Computer Science, Some Notes
    (5 May 2008)
    by Jean Gallier
    posted to mathematics machine-learning by markusd on 2008-05-07 16:50:22 as ** along with 3 people jrw pdlug ansobol
  • What is principal component analysis?
    Nature Biotechnology, Vol. 26, No. 3., pp. 303-304.
    by Markus Ringnér
    posted to pca machine-learning by markusd on 2008-05-07 16:46:48 as ** along with 45 people and 3 groups laharrin chrissp100 xingxu dekay23 rvosa i-stevenson dimka dayjm ashko craigwilson06 abbie_riner quianominorleo bibay2004 jfr kristgy pavanghatty rchauhan waghsk hpaces adacier fryanpan sobolevnrm Yanno jyuh operon barry baaic dullhunk Bevan_Weir zeji gareth massivemayhem zwang GustavoLacerda GeeSharpMinor bmaust zambujo mingzhi starz1010101 maralena wchannels sunhwan jennifermbui kdelavega zhouyu FAB-lab Bioinformatics baker-group
  • Probabilistic inference using Markov chain Monte Carlo methods
    (25 September 1993)
    by Radford M Neal
    posted to mcmc machine-learning by markusd on 2008-05-07 16:46:31 as ** along with 1 person and 1 group ldietz Skill-Inference
  • Getting Started in Probabilistic Graphical Models
    PLoS Computational Biology, Vol. 3, No. 12. (December 2007), pp. 2421-2425.
    by Edoardo M Airoldi
    posted to machine-learning by markusd on 2008-05-07 16:45:05 as ** along with 1 person ldietz
  • Markov Chain Monte Carlo in Practice
    (01 December 1995)
    by WR Gilks
    posted to mcmc machine-learning by markusd on 2008-05-07 16:44:57 as ** along with 11 people and 1 group abbie_riner ldietz fredguilloux rpadams eme Borelli metamerist wasteland93 lcigler Xavier roys astro
  • The Bayesian Choice
    (2007)
    by C Robert
    posted to machine-learning by markusd on 2008-05-07 16:43:18 as ** along with 1 person pcarbo
  • Metropolized independent sampling with comparisons to rejection sampling and importance sampling
    Statistics and Computing, Vol. 6, No. 2. (1 June 1996), pp. 113-119.
    by Jun S Liu
    posted to mcmc machine-learning gibbs by markusd on 2008-05-07 16:43:09 as ** along with 1 person pcarbo
  • Markov Chain Monte Carlo Method and Its Application
    by Stephen P Brooks
    posted to mcmc machine-learning gibbs by markusd on 2008-05-07 16:42:57 as ** along with 3 people icosma alexv Xavier
  • Monte Carlo Sampling Methods Using Markov Chains and Their Applications
    Biometrika, Vol. 57, No. 1. (1970), pp. 97-109.
    by WK Hastings
    posted to mcmc machine-learning gibbs by markusd on 2008-05-07 16:42:48 as ** along with 4 people bfraser icosma rabio lcigler
  • Markov Chain Monte Carlo in Practice: A Roundtable Discussion
    The American Statistician, Vol. 52, No. 2. (1998), pp. 93-100.
    by Robert E Kass, Bradley P Carlin, Andrew Gelman, Radford M Neal
    posted to mcmc machine-learning gibbs by markusd on 2008-05-07 16:42:39 as ** along with 3 people i-stevenson ddahlem icosma
  • Facilitating the Gibbs Sampler: The Gibbs Stopper and the Griddy-Gibbs Sampler
    Journal of the American Statistical Association, Vol. 87, No. 419. (1992), pp. 861-868.
    by Christian Ritter, Martin A Tanner
    posted to mcmc machine-learning gibbs by markusd on 2008-05-07 16:42:24 as ** along with 1 person icosma
  • Bayesian Statistics without Tears: A Sampling-Resampling Perspective
    The American Statistician, Vol. 46, No. 2. (1992), pp. 84-88.
    by AFM Smith, AE Gelfand
    posted to mcmc machine-learning gibbs by markusd on 2008-05-07 16:42:12 as ** along with 2 people abbie_riner icosma
  • The Calculation of Posterior Distributions by Data Augmentation
    Journal of the American Statistical Association, Vol. 82, No. 398. (1987), pp. 528-540.
    by Martin A Tanner, Wing H Wong
    posted to machine-learning by markusd on 2008-05-07 16:41:56 as ** along with 4 people and 1 group abbie_riner icosma plm rharang SAA-HSA
  • Hierarchical structure and the prediction of missing links in networks
    Nature, Vol. 453, No. 7191., pp. 98-101.
    by Aaron Clauset, Cristopher Moore, MEJ Newman
    posted to machine-learning by markusd on 2008-05-07 16:36:05 as ** along with 24 people pbull jago Ema gtgt15 hryk nedwards i-stevenson pinney elsantosneto eyliu craigwilson06 jyuh margaritis gagliol bryanhughes akshat tmmurali cactus AbnerCYH tny briordan deanmalmgren soramame_0518 jjray
  • Understanding the Metropolis-Hastings Algorithm
    The American Statistician, Vol. 49, No. 4. (1995), pp. 327-335.
    by Siddhartha Chib, Edward Greenberg
    posted to machine-learning by markusd on 2008-05-07 16:30:50 as ** along with 10 people and 3 groups quianominorleo jrw rvosa i-stevenson nojhan ldietz pcarbo icosma adriandefroment leonnovelo FAB-lab Metaheuristics Skill-Inference
  • Learning Dynamic Bayesian Networks
    Lecture Notes in Computer Science, Vol. 1387 (1998), pp. 168-197.
    by Zoubin Ghahramani
    posted to machine-learning by markusd on 2008-05-06 20:33:21 as ** along with 1 person pthimon
  • Accelerated training of conditional random fields with stochastic gradient methods
    (2006)
    by Nicol N Vishwanathan
    posted to machine-learning by markusd on 2008-05-01 00:23:49 as ** along with 1 person whym
  • Composition of Conditional Random Fields for Transfer Learning
    (October 2005), pp. 748-754.
    by Charles Sutton, Andrew Mccallum
    posted to machine-learning by markusd on 2008-05-01 00:21:55 as **
  • Bootstrapping Without the Boot
    (October 2005), pp. 395-402.
    by Jason Eisner, Damianos Karakos
    posted to machine-learning by markusd on 2008-05-01 00:13:53 as **
  • Part-of-Speech Tagging using Virtual Evidence and Negative Training
    (October 2005), pp. 459-466.
    by Sheila M Reynolds, Jeff A Bilmes
    posted to machine-learning file-import-08-05-01 by markusd on 2008-05-01 00:06:47 as **
  • Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
    Biometrika, Vol. 82 (1995), pp. 711-732.
    by P Green
    posted to machine-learning by markusd on 2008-04-11 20:41:47 as ** along with 2 people rpadams OscarRueda
  • Combinatorial Stochastic Processes
    (2002)
    by J Pitman
    posted to machine-learning by markusd on 2008-04-09 16:26:34 as ** along with 1 person jsr
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