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    » Overlapping Variance Estimators for Simulation
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    ANSS
    1996
    IEEE
    134views Modeling and Simulation» more  ANSS 1996»
    Computation of the Asymptotic Bias and Variance for Simulation of Markov Reward Models
    13 years 11 months ago
    Computation of the Asymptotic Bias and Variance for Simulation of Markov Reward Models
    Download  www.cs.ncl.ac.uk
    The asymptotic bias and variance are important determinants of the quality of a simulation run. In particular, the asymptotic bias can be used to approximate the bias introduced b...
    Aad P. A. van Moorsel, Latha A. Kant, William H. S...
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    NIPS
    2001
    144views Information Technology» more  NIPS 2001»
    Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
    13 years 8 months ago
    Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
    Download  jmlr.csail.mit.edu
    Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
    Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
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    TSP
    2008
    178views more  TSP 2008»
    Monte Carlo Methods for Channel, Phase Noise, and Frequency Offset Estimation With Unknown Noise Variances in OFDM Systems
    13 years 7 months ago
    Monte Carlo Methods for Channel, Phase Noise, and Frequency Offset Estimation With Unknown Noise Variances in OFDM Systems
    Download  www-sigproc.eng.cam.ac.uk
    In this paper, we address the problem of orthogonal frequency-division multiplexing (OFDM) channel estimation in the presence of phase noise (PHN) and carrier frequency offset (CFO...
    F. Septier, Yves Delignon, A. Menhaj-Rivenq, Chris...
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    WSC
    2007
    104views Modeling And Simulation» more  WSC 2007»
    Low bias integrated path estimators
    13 years 9 months ago
    Low bias integrated path estimators
    Download  www.informs-sim.org
    We consider the problem of estimating the time-average variance constant for a stationary process. A previous paper described an approach based on multiple integrations of the sim...
    James M. Calvin
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    WSC
    2007
    234views Modeling And Simulation» more  WSC 2007»
    Feasibility study of variance reduction in the logistics composite model
    13 years 9 months ago
    Feasibility study of variance reduction in the logistics composite model
    Download  www.informs-sim.org
    The Logistics Composite Model (LCOM) is a stochastic, discrete-event simulation that relies on probabilities and random number generators to model scenarios in a maintenance unit ...
    George P. Cole III, Alan W. Johnson, J. O. Miller
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