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    NIPS
    2001
    210views Information Technology» more  NIPS 2001»
    Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
    13 years 9 months ago
    Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
    Download  research.microsoft.com
    This paper develops a new approach for extremely fast detection in domains where the distribution of positive and negative examples is highly skewed (e.g. face detection or databa...
    Paul A. Viola, Michael J. Jones
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    NIPS
    2001
    146views Information Technology» more  NIPS 2001»
    Sequential Noise Compensation by Sequential Monte Carlo Method
    13 years 9 months ago
    Sequential Noise Compensation by Sequential Monte Carlo Method
    Download  books.nips.cc
    We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...
    K. Yao, S. Nakamura
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    IJCAI
    2003
    134views Artificial Intelligence» more  IJCAI 2003»
    DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks
    13 years 9 months ago
    DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks
    Download  web.mit.edu
    We present a novel, laser range finder based algorithm for simultaneous localization and mapping (SLAM) for mobile robots. SLAM addresses the problem of constructing an accurate ...
    Austin I. Eliazar, Ronald Parr
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    UAI
    2004
    134views Artificial Intelligence» more  UAI 2004»
    Convolutional Factor Graphs as Probabilistic Models
    13 years 9 months ago
    Convolutional Factor Graphs as Probabilistic Models
    Download  www.site.uottawa.ca
    Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
    Yongyi Mao, Frank R. Kschischang, Brendan J. Frey
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    NIPS
    2003
    130views Information Technology» more  NIPS 2003»
    Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
    13 years 9 months ago
    Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
    Download  books.nips.cc
    We describe a Markov chain method for sampling from the distribution of the hidden state sequence in a non-linear dynamical system, given a sequence of observations. This method u...
    Radford M. Neal, Matthew J. Beal, Sam T. Roweis
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