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    AAAI
    2008
    157views Intelligent Agents» more  AAAI 2008»
    Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks
    13 years 11 months ago
    Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks
    Download  www.aaai.org
    Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...
    Cédric Rose, Jamal Saboune, François...
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    AAAI
    2008
    132views Intelligent Agents» more  AAAI 2008»
    Phase Transitions and Complexity of Weighted Satisfiability and Other Intractable Parameterized Problems
    13 years 11 months ago
    Phase Transitions and Complexity of Weighted Satisfiability and Other Intractable Parameterized Problems
    Download  www.aaai.org
    The study of random instances of NP complete and coNP complete problems has had much impact on our understanding of the nature of hard problems. In this work, we initiate an effor...
    Yong Gao
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    AAAI
    1998
    146views Intelligent Agents» more  AAAI 1998»
    Structured Representation of Complex Stochastic Systems
    13 years 10 months ago
    Structured Representation of Complex Stochastic Systems
    Download  ai.stanford.edu
    This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
    Nir Friedman, Daphne Koller, Avi Pfeffer
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    MP
    2011
    206views Intelligent Agents» more  MP 2011»
    Smoothed analysis of condition numbers and complexity implications for linear programming
    13 years 3 months ago
    Smoothed analysis of condition numbers and complexity implications for linear programming
    Download  www.cs.yale.edu
    We perform a smoothed analysis of Renegar’s condition number for linear programming by analyzing the distribution of the distance to ill-posedness of a linear program subject to...
    John Dunagan, Daniel A. Spielman, Shang-Hua Teng
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    ICAART
    2010
    INSTICC
    509views Intelligent Agents» more  ICAART 2010»
    Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
    14 years 5 months ago
    Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
    Download  arxiv.org
    There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
    Christos Dimitrakakis
    posted by olethros
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