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    » The Weighted Majority Algorithm
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    STOC
    2007
    ACM
    98views Algorithms» more  STOC 2007»
    Negative weights make adversaries stronger
    14 years 9 months ago
    Negative weights make adversaries stronger
    Download  www1.cs.columbia.edu
    The quantum adversary method is one of the most successful techniques for proving lower bounds on quantum query complexity. It gives optimal lower bounds for many problems, has ap...
    Peter Høyer, Troy Lee, Robert Spalek
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    JMLR
    2012
    253views Programming Languages» more  JMLR 2012»
    Graphlet decomposition of a weighted network
    11 years 11 months ago
    Graphlet decomposition of a weighted network
    Download  jmlr.csail.mit.edu
    We introduce the graphlet decomposition of a weighted network, which encodes a notion of social information based on social structure. We develop a scalable algorithm, which combi...
    Hossein Azari Soufiani, Edo Airoldi
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    ICC
    2008
    IEEE
    112views Communications» more  ICC 2008»
    Weighted Fair Uplink/Downlink Access Provisioning in IEEE 802.11e WLANs
    14 years 3 months ago
    Weighted Fair Uplink/Downlink Access Provisioning in IEEE 802.11e WLANs
    Download  www.ece.uci.edu
    — We present the unfairness problem between the uplink and the downlink flows in the IEEE 802.11e infrastructure Basic Service Set (BSS) when the default settings of the Enhance...
    Feyza Keceli, Inanc Inan, Ender Ayanoglu
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    GLOBECOM
    2007
    IEEE
    134views Communications» more  GLOBECOM 2007»
    Optimal Downlink OFDMA Subcarrier, Rate, and Power Allocation with Linear Complexity to Maximize Ergodic Weighted-Sum Rates
    13 years 10 months ago
    Optimal Downlink OFDMA Subcarrier, Rate, and Power Allocation with Linear Complexity to Maximize Ergodic Weighted-Sum Rates
    Download  users.ece.utexas.edu
    Abstract— In this paper, we propose a resource allocation algorithm for ergodic weighted-sum rate maximization in downlink OFDMA systems. In contrast to most previous research tha...
    Ian C. Wong, Brian L. Evans
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    MOC
    2002
    86views more  MOC 2002»
    On the step-by-step construction of quasi--Monte Carlo integration rules that achieve strong tractability error bounds in weight
    13 years 8 months ago
    On the step-by-step construction of quasi--Monte Carlo integration rules that achieve strong tractability error bounds in weight
    Download  www.ams.org
    We develop and justify an algorithm for the construction of quasi
    Ian H. Sloan, Frances Y. Kuo, Stephen Joe
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