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    ICML
    2006
    IEEE
    248views Machine Learning» more  ICML 2006»
    R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization
    14 years 5 months ago
    R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization
    Download  ranger.uta.edu
    Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
    Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan...
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    ICML
    2006
    IEEE
    104views Machine Learning» more  ICML 2006»
    Efficient learning of Naive Bayes classifiers under class-conditional classification noise
    14 years 5 months ago
    Efficient learning of Naive Bayes classifiers under class-conditional classification noise
    Download  delivery.acm.org
    We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
    Christophe Nicolas Magnan, François Denis, ...
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    ICML
    2006
    IEEE
    156views Machine Learning» more  ICML 2006»
    Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
    14 years 5 months ago
    Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
    Download  animatlab.lip6.fr
    Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
    Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
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    ICML
    2006
    IEEE
    122views Machine Learning» more  ICML 2006»
    The relationship between Precision-Recall and ROC curves
    14 years 5 months ago
    The relationship between Precision-Recall and ROC curves
    Download  pages.cs.wisc.edu
    Receiver Operator Characteristic (ROC) curves are commonly used to present results for binary decision problems in machine learning. However, when dealing with highly skewed datas...
    Jesse Davis, Mark Goadrich
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    ICML
    2006
    IEEE
    182views Machine Learning» more  ICML 2006»
    Locally adaptive classification piloted by uncertainty
    14 years 5 months ago
    Locally adaptive classification piloted by uncertainty
    Download  mmlab.ie.cuhk.edu.hk
    Locally adaptive classifiers are usually superior to the use of a single global classifier. However, there are two major problems in designing locally adaptive classifiers. First,...
    Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwo...
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    ICML
    2006
    IEEE
    117views Machine Learning» more  ICML 2006»
    A continuation method for semi-supervised SVMs
    14 years 5 months ago
    A continuation method for semi-supervised SVMs
    Download  www.kyb.tuebingen.mpg.de
    Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
    Olivier Chapelle, Mingmin Chi, Alexander Zien
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    ICML
    2006
    IEEE
    117views Machine Learning» more  ICML 2006»
    Hierarchical classification: combining Bayes with SVM
    14 years 5 months ago
    Hierarchical classification: combining Bayes with SVM
    Download  www.dicom.uninsubria.it
    We study hierarchical classification in the general case when an instance could belong to more than one class node in the underlying taxonomy. Experiments done in previous work sh...
    Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
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    ICML
    2006
    IEEE
    108views Machine Learning» more  ICML 2006»
    Robust Euclidean embedding
    14 years 5 months ago
    Robust Euclidean embedding
    Download  cseweb.ucsd.edu
    We derive a robust Euclidean embedding procedure based on semidefinite programming that may be used in place of the popular classical multidimensional scaling (cMDS) algorithm. We...
    Lawrence Cayton, Sanjoy Dasgupta
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    ICML
    2006
    IEEE
    171views Machine Learning» more  ICML 2006»
    An empirical comparison of supervised learning algorithms
    14 years 5 months ago
    An empirical comparison of supervised learning algorithms
    Download  www.cs.cornell.edu
    A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
    Rich Caruana, Alexandru Niculescu-Mizil
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    ICML
    2006
    IEEE
    85views Machine Learning» more  ICML 2006»
    Fast nonparametric clustering with Gaussian blurring mean-shift
    14 years 5 months ago
    Fast nonparametric clustering with Gaussian blurring mean-shift
    Download  faculty.ucmerced.edu
    Miguel Á. Carreira-Perpiñán
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