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    JMLR
    2008
    132views more  JMLR 2008»
    Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
    13 years 10 months ago
    Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
    Download  www.eecs.berkeley.edu
    Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
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    JMLR
    2008
    188views more  JMLR 2008»
    Maximal Causes for Non-linear Component Extraction
    13 years 11 months ago
    Maximal Causes for Non-linear Component Extraction
    Download  www.gatsby.ucl.ac.uk
    We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
    Jörg Lücke, Maneesh Sahani
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    JMLR
    2006
    108views more  JMLR 2006»
    The Interplay of Optimization and Machine Learning Research
    13 years 11 months ago
    The Interplay of Optimization and Machine Learning Research
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    The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
    Kristin P. Bennett, Emilio Parrado-Hernánde...
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    JMLR
    2006
    206views more  JMLR 2006»
    New Algorithms for Efficient High-Dimensional Nonparametric Classification
    13 years 11 months ago
    New Algorithms for Efficient High-Dimensional Nonparametric Classification
    Download  jmlr.csail.mit.edu
    This paper is about non-approximate acceleration of high-dimensional nonparametric operations such as k nearest neighbor classifiers. We attempt to exploit the fact that even if w...
    Ting Liu, Andrew W. Moore, Alexander G. Gray
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    JMLR
    2006
    120views more  JMLR 2006»
    Kernel-Based Learning of Hierarchical Multilabel Classification Models
    13 years 11 months ago
    Kernel-Based Learning of Hierarchical Multilabel Classification Models
    Download  jmlr.csail.mit.edu
    We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
    Juho Rousu, Craig Saunders, Sándor Szedm&aa...
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    JMLR
    2006
    103views more  JMLR 2006»
    A Graphical Representation of Equivalence Classes of AMP Chain Graphs
    13 years 11 months ago
    A Graphical Representation of Equivalence Classes of AMP Chain Graphs
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    This paper deals with chain graph models under alternative AMP interpretation. A new representative of an AMP Markov equivalence class, called the largest deflagged graph, is prop...
    Alberto Roverato, Milan Studený
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    JMLR
    2006
    136views more  JMLR 2006»
    Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
    13 years 11 months ago
    Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
    Download  jmlr.csail.mit.edu
    In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
    Tonatiuh Peña Centeno, Neil D. Lawrence
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    JMLR
    2006
    389views more  JMLR 2006»
    A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
    13 years 11 months ago
    A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
    Download  jmlr.csail.mit.edu
    This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
    Enrique Castillo, Bertha Guijarro-Berdiñas,...
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    JMLR
    2006
    124views more  JMLR 2006»
    Policy Gradient in Continuous Time
    13 years 11 months ago
    Policy Gradient in Continuous Time
    Download  hal.inria.fr
    Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...
    Rémi Munos
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    JMLR
    2006
    150views more  JMLR 2006»
    Building Support Vector Machines with Reduced Classifier Complexity
    13 years 11 months ago
    Building Support Vector Machines with Reduced Classifier Complexity
    Download  jmlr.csail.mit.edu
    Support vector machines (SVMs), though accurate, are not preferred in applications requiring great classification speed, due to the number of support vectors being large. To overc...
    S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCos...
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