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    ALT
    2008
    Springer
    152views Machine Learning» more  ALT 2008»
    Active Learning of Group-Structured Environments
    14 years 1 months ago
    Active Learning of Group-Structured Environments
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    The question investigated in this paper is to what extent an input representation influences the success of learning, in particular from the point of view of analyzing agents that...
    Gábor Bartók, Csaba Szepesvár...
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    IANDC
    2010
    45views more  IANDC 2010»
    Models of active learning in group-structured state spaces
    13 years 3 months ago
    Models of active learning in group-structured state spaces
    Download  www.ualberta.ca
    Gábor Bartók, Csaba Szepesvár...
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    INFORMS
    1998
    142views more  INFORMS 1998»
    Distributed State Space Generation of Discrete-State Stochastic Models
    13 years 4 months ago
    Distributed State Space Generation of Discrete-State Stochastic Models
    Download  www.cs.ucr.edu
    High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models often requires the generatio...
    Gianfranco Ciardo, Joshua Gluckman, David M. Nicol
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    TSP
    2011
    197views more  TSP 2011»
    Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods
    12 years 12 months ago
    Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods
    Download  www.lancs.ac.uk
    —This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems fr...
    Amadou Gning, Lyudmila Mihaylova, Simon Maskell, S...
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    NIPS
    1998
    117views Information Technology» more  NIPS 1998»
    Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
    13 years 6 months ago
    Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
    Download  www.gatsby.ucl.ac.uk
    We present Monte-Carlo generalized EM equations for learning in nonlinear state space models. The dif
    Thomas Briegel, Volker Tresp
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