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anoopsarkar's learning [15 articles]

Recent papers added to anoopsarkar's library classified by the tag learning. You can also see everyone's learning.
  • An overview of statistical learning theory
    Neural Networks, IEEE Transactions on, Vol. 10, No. 5. (1999), pp. 988-999.
    by VN Vapnik
    posted to learning by anoopsarkar on 2005-11-13 17:46:27 as *** along with 16 people and 9 groups fredguilloux sourada A_Olympia yaroslavvb gangli eme garyfeng arsyed yish sdvillal gane5h dwf atbrew d_burfoot rsantana balduzzi Philosophy_of_Information Blog_and_Wiki_Research tulip ReadingLab astro mathgamespatterns dtl vds-arg eni
  • A Tutorial on the Expectation-Maximization Algorithm Including Maximum-Likelihood Estimation and EM Training of Probabilistic Context-Free Grammars
    (11 March 2005)
    by Detlef Prescher
    posted to em-algorithm learning by anoopsarkar on 2005-03-15 17:16:28 as read along with 1 person ejmeij
  • Boosting the margin: A New Explanation for the Effectiveness of Voting Methods
    The Annals of Statistics, Vol. 26, No. 5. (1998), pp. 1651-1686.
    by RE Schapire, Y Freund, P Bartlett, WS Lee
    posted to boosting learning voting by anoopsarkar on 2005-03-08 22:30:39 as read
  • Memory-based Shallow Parsing
    Journal of Machine Learning Research, Vol. 2 (March 2002), pp. 559-594.
    by EFTK Tjong
    posted to learning nlp text-chunking by anoopsarkar on 2005-03-08 22:30:39 as **
  • Text Chunking based on a Generalization of Winnow
    Journal of Machine Learning Research, Vol. 2 (March 2002), pp. 615-637.
    by T Zhang, F Damerau, D Johnson
    posted to learning nlp text-chunking by anoopsarkar on 2005-03-08 22:30:39 as **
  • Shallow Parsing using Specialized HMMs
    Journal of Machine Learning Research, Vol. 2 (March 2002), pp. 595-613.
    by A Molina, F Pla
    posted to hidden-markov-models learning nlp text-chunking by anoopsarkar on 2005-03-08 22:30:39 as **
  • Probabilistic Functions of Finite-State Markov Chains
    Proceedings of the National Academy of Sciences of the United States of America, Vol. 57, No. 3. (1967), pp. 580-581.
    by T Petrie
    posted to hidden-markov-models learning by anoopsarkar on 2005-03-08 22:21:01 as ** along with 1 person goodienough
  • Hidden Markov Random Fields
    The Annals of Applied Probability, Vol. 5, No. 3. (1995), pp. 577-602.
    by Hans Kunsch, Stuart Geman, Athanasios Kehagias
    posted to hidden-markov-models learning by anoopsarkar on 2005-03-08 22:19:41 as **** along with 7 people and 1 group arkas unnonouno syoyo Kazuki suizan yangxian shabib UoA_ODT
  • A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
    The Annals of Mathematical Statistics, Vol. 41, No. 1. (1970), pp. 164-171.
    by Leonard E Baum, Ted Petrie, George Soules, Norman Weiss
    posted to em-algorithm hidden-markov-models learning by anoopsarkar on 2005-03-08 22:18:39 as ** along with 3 people ecome goodienough johnkork
  • On the Convergence of the EM Algorithm
    Journal of the Royal Statistical Society. Series B (Methodological), Vol. 45, No. 1. (1983), pp. 47-50.
    by Russell A Boyles
    posted to em-algorithm learning by anoopsarkar on 2005-03-08 22:14:15 as read along with 1 person olivierbousquet
  • On the Convergence Properties of the EM Algorithm
    The Annals of Statistics, Vol. 11, No. 1. (1983), pp. 95-103.
    by Jeff FJ Wu
    posted to em-algorithm learning by anoopsarkar on 2005-03-08 22:13:20 as read along with 3 people davidr tvdbulck juokcho
  • Conjugate Gradient Acceleration of the EM Algorithm
    Journal of the American Statistical Association, Vol. 88, No. 421. (1993), pp. 221-228.
    by Mortaza Jamshidian, Robert I Jennrich
    posted to em-algorithm learning by anoopsarkar on 2005-03-08 22:11:45 as ****
  • Acceleration of the EM Algorithm by Using Quasi-Newton Methods
    Journal of the Royal Statistical Society. Series B (Methodological), Vol. 59, No. 3. (1997), pp. 569-587.
    by Mortaza Jamshidian, Robert I Jennrich
    posted to em-algorithm learning statistics by anoopsarkar on 2005-03-08 19:27:14 as ****
  • Maximum Likelihood from Incomplete Data via the EM Algorithm
    Journal of the Royal Statistical Society. Series B (Methodological), Vol. 39, No. 1. (1977), pp. 1-38.
    by AP Dempster, NM Laird, DB Rubin
    posted to em-algorithm learning statistics by anoopsarkar on 2005-03-08 19:21:57 as read along with 43 people and 8 groups iansimon qwermish wenhan eegilbert weymouth jake ingo gangli rpadams wkw hoangmtbk dragonrez Freyr lukec dheena songhaoyuan amirsaemi j3xucite ecome walkking nandan marrtin tvdbulck MichaelDonoser MikeDoni rwilliamson calamar qq987 ichbins81 petrposik ggorjan shiquanwang lcigler ciga kvorg ifejobi DavidSchulz ykuoka singhsh trop_wizz eddymier schulz stkhu MBLAB Statistics_and_Social_Science tulip LTN Computer_Graphics Computational_Information_Geometry csb_journal_club_public Medical Image Analysis and Visualization @ OSU
  • Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
    (01 March 1998)
    by Richard S Sutton, Andrew G Barto
    posted to learning markov-decision-processes reinforcement-learning by anoopsarkar on 2005-03-05 08:43:34 as ** along with 17 people and 2 groups fbernardo tdahl jerlich klouie oamg creswick kmregan garyfeng mrkrause stain gonium nelmor awooga mzygmunt mak bsilverthorn robotact Glimcher_Lab ReadingLab
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