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    ECML
    2007
    Springer
    133views Machine Learning» more  ECML 2007»
    Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
    14 years 5 months ago
    Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
    Download  cs.nju.edu.cn
    Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...
    Xiao-Lin Li, Zhi-Hua Zhou
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    ECML
    2007
    Springer
    129views Machine Learning» more  ECML 2007»
    Class Noise Mitigation Through Instance Weighting
    14 years 5 months ago
    Class Noise Mitigation Through Instance Weighting
    Download  www.eecs.tufts.edu
    We describe a novel framework for class noise mitigation that assigns a vector of class membership probabilities to each training instance, and uses the confidence on the current ...
    Umaa Rebbapragada, Carla E. Brodley
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    ECML
    2007
    Springer
    207views Machine Learning» more  ECML 2007»
    Dual Strategy Active Learning
    14 years 5 months ago
    Dual Strategy Active Learning
    Download  www.cs.cmu.edu
    Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...
    Pinar Donmez, Jaime G. Carbonell, Paul N. Bennett
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    ECML
    2007
    Springer
    161views Machine Learning» more  ECML 2007»
    Statistical Debugging Using Latent Topic Models
    14 years 5 months ago
    Statistical Debugging Using Latent Topic Models
    Download  pages.cs.wisc.edu
    Abstract. Statistical debugging uses machine learning to model program failures and help identify root causes of bugs. We approach this task using a novel Delta-Latent-Dirichlet-Al...
    David Andrzejewski, Anne Mulhern, Ben Liblit, Xiao...
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    ECML
    2007
    Springer
    116views Machine Learning» more  ECML 2007»
    Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators
    14 years 5 months ago
    Finding the Right Family: Parent and Child Selection for Averaged One-Dependence Estimators
    Download  www.csse.monash.edu.au
    Averaged One-Dependence Estimators (AODE) classifies by uniformly aggregating all qualified one-dependence estimators (ODEs). Its capacity to significantly improve naive Bayes...
    Fei Zheng, Geoffrey I. Webb
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    ECML
    2007
    Springer
    107views Machine Learning» more  ECML 2007»
    A Simple Lexicographic Ranker and Probability Estimator
    14 years 5 months ago
    A Simple Lexicographic Ranker and Probability Estimator
    Download  www.cs.bris.ac.uk
    Given a binary classification task, a ranker sorts a set of instances from highest to lowest expectation that the instance is positive. We propose a lexicographic ranker, LexRank,...
    Peter A. Flach, Edson Takashi Matsubara
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    ECML
    2007
    Springer
    187views Machine Learning» more  ECML 2007»
    Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
    14 years 5 months ago
    Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
    Download  pages.cs.wisc.edu
    L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
    Mark Schmidt, Glenn Fung, Rómer Rosales
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    DIS
    2007
    Springer
    83views Theoretical Computer Science» more  DIS 2007»
    Discovering Communicable Models from Earth Science Data
    14 years 5 months ago
    Discovering Communicable Models from Earth Science Data
    Download  ti.arc.nasa.gov
    Abstract. This chapter describes how we used regression rules to improve upon results previously published in the Earth science literature. In such a scientific application of mac...
    Mark Schwabacher, Pat Langley, Christopher Potter,...
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    COLT
    2007
    Springer
    174views Machine Learning» more  COLT 2007»
    Regret to the Best vs. Regret to the Average
    14 years 5 months ago
    Regret to the Best vs. Regret to the Average
    Download  www.math.tau.ac.il
    Abstract. We study online regret minimization algorithms in a bicriteria setting, examining not only the standard notion of regret to the best expert, but also the regret to the av...
    Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, ...
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    COLT
    2007
    Springer
    112views Machine Learning» more  COLT 2007»
    When Is There a Free Matrix Lunch?
    14 years 5 months ago
    When Is There a Free Matrix Lunch?
    Download  users.soe.ucsc.edu
    Manfred K. Warmuth
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