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    ICRA
    2006
    IEEE
    131views Robotics» more  ICRA 2006»
    Using Reinforcement Learning to Improve Exploration Trajectories for Error Minimization
    14 years 1 months ago
    Using Reinforcement Learning to Improve Exploration Trajectories for Error Minimization
    Download  mapleleaf.csail.mit.edu
    Abstract— The mapping and localization problems have received considerable attention in robotics recently. The exploration problem that drives mapping has started to generate sim...
    Thomas Kollar, Nicholas Roy
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    ICCBR
    2010
    Springer
    274views Automated Reasoning» more  ICCBR 2010»
    Reducing the Memory Footprint of Temporal Difference Learning over Finitely Many States by Using Case-Based Generalization
    13 years 11 months ago
    Reducing the Memory Footprint of Temporal Difference Learning over Finitely Many States by Using Case-Based Generalization
    Download  www.cse.lehigh.edu
    In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...
    Matt Dilts, Héctor Muñoz-Avila
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    IJCV
    2007
    196views more  IJCV 2007»
    Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
    13 years 7 months ago
    Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
    Download  people.csail.mit.edu
    We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
    Robert Fergus, Pietro Perona, Andrew Zisserman
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    ACCV
    2006
    Springer
    174views Computer Vision» more  ACCV 2006»
    Learning Multi-category Classification in Bayesian Framework
    13 years 9 months ago
    Learning Multi-category Classification in Bayesian Framework
    Download  www.research.rutgers.edu
    Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
    Atul Kanaujia, Dimitris N. Metaxas
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    TJS
    2010
    182views more  TJS 2010»
    A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
    13 years 6 months ago
    A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
    Download  ceit.aut.ac.ir
    This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
    Yasser Yasami, Saadat Pour Mozaffari
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