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    FOCS
    2007
    IEEE
    135views Theoretical Computer Science» more  FOCS 2007»
    On the Advantage over Random for Maximum Acyclic Subgraph
    14 years 3 months ago
    On the Advantage over Random for Maximum Acyclic Subgraph
    Download  www.cs.princeton.edu
    In this paper we present a new approximation algorithm for the Max Acyclic Subgraph problem. Given an instance where the maximum acyclic subgraph contains 1/2 + δ fraction of all...
    Moses Charikar, Konstantin Makarychev, Yury Makary...
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    CCE
    2004
    108views Software Engineering» more  CCE 2004»
    Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
    13 years 9 months ago
    Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
    Download  www.vri-custom.org
    This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
    José María Ponce-Ortega, Vicente Ric...
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    NIPS
    1998
    164views Information Technology» more  NIPS 1998»
    Approximate Learning of Dynamic Models
    13 years 10 months ago
    Approximate Learning of Dynamic Models
    Download  robotics.stanford.edu
    Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
    Xavier Boyen, Daphne Koller
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    JAIR
    2000
    152views more  JAIR 2000»
    Value-Function Approximations for Partially Observable Markov Decision Processes
    13 years 9 months ago
    Value-Function Approximations for Partially Observable Markov Decision Processes
    Download  www.cs.pitt.edu
    Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
    Milos Hauskrecht
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    TWC
    2008
    135views more  TWC 2008»
    Optimal Distributed Stochastic Routing Algorithms for Wireless Multihop Networks
    13 years 9 months ago
    Optimal Distributed Stochastic Routing Algorithms for Wireless Multihop Networks
    Download  www.seas.upenn.edu
    A novel framework was introduced recently for stochastic routing in wireless multihop networks, whereby each node selects a neighbor to forward a packet according to a probability...
    Alejandro Ribeiro, Nikolas D. Sidiropoulos, Georgi...
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