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    CDC
    2009
    IEEE
    97views Control Systems» more  CDC 2009»
    On the queue-overflow probabilities of distributed scheduling algorithms
    15 years 10 months ago
    On the queue-overflow probabilities of distributed scheduling algorithms
    Download  cobweb.ecn.purdue.edu
    Abstract-- In this paper, we are interested in using largedeviations theory to characterize the asymptotic decay-rate of the queue-overflow probability for distributed wireless sch...
    Can Zhao, Xiaojun Lin
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    VMV
    2008
    151views Visualization» more  VMV 2008»
    Adaptive surface decomposition for the distance computation of arbitrarily shaped objects
    15 years 8 months ago
    Adaptive surface decomposition for the distance computation of arbitrarily shaped objects
    Download  cg.informatik.uni-freiburg.de
    We propose an adaptive decomposition algorithm to compute separation distances between arbitrarily shaped objects. Using the Gilbert-JohnsonKeerthi algorithm (GJK), we search for ...
    Marc Gissler, Matthias Teschner
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    AAAI
    2006
    121views Intelligent Agents» more  AAAI 2006»
    Focused Real-Time Dynamic Programming for MDPs: Squeezing More Out of a Heuristic
    15 years 8 months ago
    Focused Real-Time Dynamic Programming for MDPs: Squeezing More Out of a Heuristic
    Download  www.cs.cmu.edu
    Real-time dynamic programming (RTDP) is a heuristic search algorithm for solving MDPs. We present a modified algorithm called Focused RTDP with several improvements. While RTDP ma...
    Trey Smith, Reid G. Simmons
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    DAGSTUHL
    2004
    105views Software Engineering» more  DAGSTUHL 2004»
    On the Complexity of Parabolic Initial Value Problems with Variable Drift
    15 years 8 months ago
    On the Complexity of Parabolic Initial Value Problems with Variable Drift
    Download  drops.dagstuhl.de
    We study the intrinsic difficulty of solving linear parabolic initial value problems numerically at a single point. We present a worst case analysis for deterministic as well as fo...
    Knut Petras, Klaus Ritter
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    UAI
    1998
    123views Artificial Intelligence» more  UAI 1998»
    Large Deviation Methods for Approximate Probabilistic Inference
    15 years 8 months ago
    Large Deviation Methods for Approximate Probabilistic Inference
    Download  www.cis.upenn.edu
    We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
    Michael J. Kearns, Lawrence K. Saul
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