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    TSP
    2012
    344views Artificial Intelligence» more  TSP 2012»
    Distributed Covariance Estimation in Gaussian Graphical Models
    12 years 3 months ago
    Distributed Covariance Estimation in Gaussian Graphical Models
    Download  www.cs.huji.ac.il
    —We consider distributed estimation of the inverse covariance matrix in Gaussian graphical models. These models factorize the multivariate distribution and allow for efficient d...
    Ami Wiesel, Alfred O. Hero
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    NIPS
    2007
    136views Information Technology» more  NIPS 2007»
    Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
    13 years 9 months ago
    Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
    Download  books.nips.cc
    We introduce a functional representation of time series which allows forecasts to be performed over an unspecified horizon with progressively-revealed information sets. By virtue...
    Nicolas Chapados, Yoshua Bengio
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    WCE
    2007
    183views Electrical And Computer Engi...» more  WCE 2007»
    Transformation Model Estimation for Point Matching Via Gaussian Processes
    13 years 9 months ago
    Transformation Model Estimation for Point Matching Via Gaussian Processes
    Download  www.iaeng.org
    —One of main issues in point matching is the choice of the mapping function and the computation of its optimal hyperparameters. In this paper, we propose an attractive approach t...
    Xin Yu, Jin-Wen Tian, Jian Liu
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    SAC
    2008
    ACM
    80views Applied Computing» more  SAC 2008»
    Curve prediction and clustering with mixtures of Gaussian process functional regression models
    13 years 7 months ago
    Curve prediction and clustering with mixtures of Gaussian process functional regression models
    Download  www.staff.ncl.ac.uk
    J. Q. Shi, B. Wang
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    NIPS
    2003
    289views Information Technology» more  NIPS 2003»
    Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
    13 years 9 months ago
    Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
    Download  books.nips.cc
    In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
    Neil D. Lawrence
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