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    JMLR
    2008
    111views more  JMLR 2008»
    Ranking Categorical Features Using Generalization Properties
    13 years 11 months ago
    Ranking Categorical Features Using Generalization Properties
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    Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
    Sivan Sabato, Shai Shalev-Shwartz
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    JMLR
    2008
    110views more  JMLR 2008»
    Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods
    13 years 11 months ago
    Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods
    Download  jmlr.csail.mit.edu
    We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
    Matthias W. Seeger
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    JMLR
    2008
    141views more  JMLR 2008»
    Accelerated Neural Evolution through Cooperatively Coevolved Synapses
    13 years 11 months ago
    Accelerated Neural Evolution through Cooperatively Coevolved Synapses
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    Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
    Faustino J. Gomez, Jürgen Schmidhuber, Risto ...
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    JMLR
    2008
    127views more  JMLR 2008»
    Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming
    13 years 11 months ago
    Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming
    Download  jmlr.csail.mit.edu
    The use of computational models is increasingly expected to play an important role in predicting the behaviour of biological systems. Models are being sought at different scales o...
    Ashwin Srinivasan, Ross D. King
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    JMLR
    2008
    159views more  JMLR 2008»
    Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
    13 years 11 months ago
    Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
    Download  www.cs.cmu.edu
    When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
    Andreas Krause, Ajit Paul Singh, Carlos Guestrin
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    JMLR
    2008
    133views more  JMLR 2008»
    Algorithms for Sparse Linear Classifiers in the Massive Data Setting
    13 years 11 months ago
    Algorithms for Sparse Linear Classifiers in the Massive Data Setting
    Download  jmlr.csail.mit.edu
    Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
    Suhrid Balakrishnan, David Madigan
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    JMLR
    2008
    73views more  JMLR 2008»
    On the Suitable Domain for SVM Training in Image Coding
    13 years 11 months ago
    On the Suitable Domain for SVM Training in Image Coding
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    Conventional SVM-based image coding methods are founded on independently restricting the distortion in every image coefficient at some particular image representation. Geometrical...
    Gustavo Camps-Valls, Juan Gutierrez, Gabriel G&oac...
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    JMLR
    2008
    100views more  JMLR 2008»
    Hit Miss Networks with Applications to Instance Selection
    13 years 11 months ago
    Hit Miss Networks with Applications to Instance Selection
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    In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
    Elena Marchiori
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    JMLR
    2008
    230views more  JMLR 2008»
    Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
    13 years 11 months ago
    Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
    Download  www.stat.berkeley.edu
    Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
    Michael Collins, Amir Globerson, Terry Koo, Xavier...
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    JMLR
    2008
    169views more  JMLR 2008»
    Multi-class Discriminant Kernel Learning via Convex Programming
    13 years 11 months ago
    Multi-class Discriminant Kernel Learning via Convex Programming
    Download  jmlr.csail.mit.edu
    Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
    Jieping Ye, Shuiwang Ji, Jianhui Chen
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