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    NECO
    2011
    182views Computer Networks» more  NECO 2011»
    Least Squares Estimation Without Priors or Supervision
    13 years 4 months ago
    Least Squares Estimation Without Priors or Supervision
    Download  www.cns.nyu.edu
    Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
    Martin Raphan, Eero P. Simoncelli
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    JMLR
    2012
    223views Programming Languages» more  JMLR 2012»
    Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
    12 years 7 days ago
    Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
    Download  www.cs.helsinki.fi
    We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situat...
    Michael Gutmann, Aapo Hyvärinen
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    JAIR
    1998
    198views more  JAIR 1998»
    Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
    13 years 9 months ago
    Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
    Download  www.jair.org
    This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
    Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
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    PROMISE
    2010
    179views Software Engineering» more  PROMISE 2010»
    Prediction of defect distribution based on project characteristics for proactive project management
    13 years 4 months ago
    Prediction of defect distribution based on project characteristics for proactive project management
    Download  promisedata.org
    As software has been pervasive and various software projects have been executed since the 1970s, software project management has played a significant role in software industry. Th...
    Youngki Hong, Wondae Kim, Jeongsoo Joo
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    TSP
    2008
    178views more  TSP 2008»
    Monte Carlo Methods for Channel, Phase Noise, and Frequency Offset Estimation With Unknown Noise Variances in OFDM Systems
    13 years 9 months ago
    Monte Carlo Methods for Channel, Phase Noise, and Frequency Offset Estimation With Unknown Noise Variances in OFDM Systems
    Download  www-sigproc.eng.cam.ac.uk
    In this paper, we address the problem of orthogonal frequency-division multiplexing (OFDM) channel estimation in the presence of phase noise (PHN) and carrier frequency offset (CFO...
    F. Septier, Yves Delignon, A. Menhaj-Rivenq, Chris...
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