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    » An ACO Algorithm for the Most Probable Explanation Problem
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    NIPS
    2008
    136views Information Technology» more  NIPS 2008»
    Clusters and Coarse Partitions in LP Relaxations
    13 years 9 months ago
    Clusters and Coarse Partitions in LP Relaxations
    Download  people.csail.mit.edu
    We propose a new class of consistency constraints for Linear Programming (LP) relaxations for finding the most probable (MAP) configuration in graphical models. Usual cluster-base...
    David Sontag, Amir Globerson, Tommi Jaakkola
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    TMM
    2008
    126views more  TMM 2008»
    Extraction of Audio Features Specific to Speech Production for Multimodal Speaker Detection
    13 years 7 months ago
    Extraction of Audio Features Specific to Speech Production for Multimodal Speaker Detection
    Download  infoscience.epfl.ch
    A method that exploits an information theoretic framework to extract optimized audio features using video information is presented. A simple measure of mutual information (MI) betw...
    Patricia Besson, Vlad Popovici, Jean-Marc Vesin, J...
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    STOC
    1993
    ACM
    117views Algorithms» more  STOC 1993»
    Efficient noise-tolerant learning from statistical queries
    14 years 1 days ago
    Efficient noise-tolerant learning from statistical queries
    Download  www.cs.iastate.edu
    In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
    Michael J. Kearns
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    JBI
    2008
    137views Bioinformatics» more  JBI 2008»
    Mining sequential patterns for protein fold recognition
    13 years 8 months ago
    Mining sequential patterns for protein fold recognition
    Download  medlab.cs.uoi.gr
    Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utiliz...
    Themis P. Exarchos, Costas Papaloukas, Christos La...
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    PAMI
    2008
    302views more  PAMI 2008»
    Learning to Detect Moving Shadows in Dynamic Environments
    13 years 8 months ago
    Learning to Detect Moving Shadows in Dynamic Environments
    Download  www-users.cs.umn.edu
    We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
    Ajay J. Joshi, Nikolaos Papanikolopoulos
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