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slacostes library [34 articles]

Neue Artikel in slacostes Bibliothek.
  • Approximate Statistical Test For Comparing Supervised Classification Learning Algorithms
    Neural Computation, Vol. 10, No. 7. (1998), pp. 1895-1923.
    by Thomas G Dietterich
    posted to experiments ml stat by slacoste on 2006-03-02 04:55:23 as **** along with 2 people robincha sugarexpletive
  • Improving Regression Estimation: Averaging Methods for Variance Reduction with Extensions to General Convex Measure Optimization
    (May 1993)
    by MP Perrone
    posted to averaging ensemble optimization by slacoste on 2005-09-14 21:46:01 as read
  • Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
    (1994), pp. 232-241.
    by SE Robertson, S Walker
    posted to 2-poisson ir by slacoste on 2005-08-17 10:02:42 as ***** along with 3 people pferguson arjen JoaquinPerez
  • Gradient-Based Learning Applied to Document Recognition
    Proceedings of the IEEE, Vol. 86, No. 11. (November 1998), pp. 2278-2324.
    by Y Lecun, L Bottou, Y Bengio, P Haffner
    posted to bibtex-import by slacoste on 2005-07-15 07:03:45 as read
  • Marginalized kernels for biological sequences
    Bioinformatics, Vol. 18, No. Suppl 1. (2002), pp. 268-275.
    by K Tsuda, T Kin, K Asai
    posted to bibtex-import by slacoste on 2005-07-15 07:03:45 as read
  • Combining SVM with graphical models for supervised classification: an introduction to Max-Margin Markov Networks
    (2003)
    by Simon Lacoste-Julien
    posted to bibtex-import m3-net by slacoste on 2005-07-15 07:03:45 as read
  • Probability: theory and examples
    (1996)
    by R Durrett
    posted to bibtex-import by slacoste on 2005-07-15 07:03:45 as read
  • Convex Optimization
    (2004)
    by Stephen Boyd, Lieven Vandenberghe
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as ****
  • Nonlinear Programming
    (1999)
    by D Bertsekas
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as ***
  • Kernel Methods for Multi-Labelled Classification and Categorical Regression Problems
    (2001)
    by Andre Elisseeff, Jason Weston
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as read
  • On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines
    Journal of Machine Learning Research, Vol. 2 (2001), pp. 265-292.
    by K Crammer, Y Singer
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as read
  • Support vector machines for multiclass pattern recognition
    (April 1999)
    by J Weston, C Watkins
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as read
  • Incorporating Invariances in Support Vector Learning Machines
    (1999)
    by Bernhard Schölkopf, Christopher Burges, Vladimir Vapnik
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • The Nature of Statistical Learning Theory
    (1999)
    by V Vapnik
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • Probabilistic Networks and Expert Systems
    (1999)
    by Robert G Cowell, Philip A Dawid, Steffen L Lauritzen, David J Spiegelhalter
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
    (2002)
    by Bernhard Schölkopf, Alexander J Smola
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as ***
  • An Introduction to Support Vector Machines and other kernel-based learning methods
    (2000)
    by Nello Cristianini, John S Taylor
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as read
  • Support-Vector Networks
    Machine Learning, Vol. 20, No. 3. (1995), pp. 273-297.
    by Corinna Cortes, Vladimir Vapnik
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • A Tutorial on Support Vector Machines for Pattern Recognition
    Data Mining and Knowledge Discovery, Vol. 2, No. 2. (1998), pp. 121-167.
    by Christopher JC Burges
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • Support Vector Machines and Kernel Methods: The New Generation of Learning Machines
    AI Magazine, Vol. 23, No. 3. (2002), pp. 31-41.
    by Nello Cristianini, Bernhard Schölkopf
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • Discriminative probabilistic models for relational data
    (2002)
    by B Taskar, P Abbeel, D Koller
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • Maximum Entropy Markov Models for Information Extraction and Segmentation
    (2000), pp. 591-598.
    by Andrew Mccallum, Dayne Freitag, Fernando Pereira
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
    (2001), pp. 282-289.
    by John Lafferty, Andrew Mccallum, Fernando Pereira
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • Learning in Graphical Models
    (1998)
    edited by Michael I Jordan
    posted to bibtex-import by slacoste on 2005-07-15 07:03:44 as **
  • An Introduction to Probabilistic Graphical Models
    (2003)
    by Michael I Jordan
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as read
  • An Algorithm that Learns What's in a Name
    Machine Learning Journal Special Issue on Natural Language Learning, Vol. 34 (1999), pp. 211-232.
    by Daniel M Bikel, Richard Schwartz, Ralph M Weischedel
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as **
  • A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
    Proceedings of the IEEE, Vol. 77, No. 2. (1989), pp. 257-286.
    by Lawrence R Rabiner
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as **
  • Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms
    (July 2002), pp. 1-8.
    by Michael Collins
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as **
  • Discriminative Learning for Label Sequences via Boosting
    (2003)
    by Yasemin Altun, Thomas Hofmann, Mark Johnson
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as **
  • Hidden Markov Support Vector Machine
    (2003)
    by Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofmann
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as read
  • Investigating Loss Functions and Optimization Methods for Discriminative Learning of Label Sequences
    (2003), pp. 145-152.
    by Yasemin Altun, Mark Johnson, Thomas Hofmann
    edited by Michael Collins, Mark Steedman
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as read
  • Large Margin Methods for Label Sequence Learning
    (2003)
    by Yasemin Altun, Thomas Hofmann
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as read
  • Machine Learning for Sequential Data: A Review
    (2002)
    by Thomas G Dietterich
    posted to bibtex-import by slacoste on 2005-07-15 07:03:43 as read
  • Max-Margin Markov Networks
    (December 2003)
    by Ben Taskar, Carlos Guestrin, Daphne Koller
    posted to bibtex-import by slacoste on 2005-07-15 07:03:38 as read
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