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31 - 40 of 61 search results for TALK:PC53 20 |u:www.statslab.cam.ac.uk where 0 match all words and 61 match some words.

  1. Results that match 1 of 2 words

  2. CHAPTER 11 Large Deviation and FluidApproximations in Controlof…

    www.statslab.cam.ac.uk/~rrw1/publications/Weber%201994%20Large%20deviations%20and%20fluid%20approximations%20in%20control%20of%20stochastic%20systems.pdf
    29 Sep 2011: For X= 3, p. = 2, e = 23.40 and <? = 22.29. For X= 2.5, p = 2.5,e = 20.63 and ef = 20.00.

  3. Concavity and Monotonicity Properties in aGroundwater Management…

    www.statslab.cam.ac.uk/~rrw1/publications/Huh%20-%20Krishnamurhty-%20Weber%202011%20Concavity%20and%20Monotonicity%20Properties%20in%20a%20Groundwater%20Management%20Model.pdf
    25 Oct 2011: the “fighter problem”, discussed in [2, 3, 20]. In this problem a fighter airplane is initially. ... Water Resource Research, 40, 2004. 06S20,. doi:10.1029/2003WR002168. [20] R. R. Weber.

  4. The Rendezvous Problem on Discrete Locations

    www.statslab.cam.ac.uk/~rrw1/publications/Anderson%20-%20Weber%201990%20The%20rendezvous%20problem%20on%20discrete%20locations.pdf
    15 Sep 2011: t= 02(n - 1 t) 20(1 - O)(n/2). n (1) (1 - )2 { p(n, O)t (n 1)(1 - p(n 1, 0)) - p(n, O) - 1.

  5. journal7.dvi

    www.statslab.cam.ac.uk/~rrw1/publications/Courcoubetis%20-%20Weber%202001%20Economic%20issues%20in%20shared%20infrastructures.pdf
    31 Oct 2011: Case (i) is common whenthe infrastructure is initially created using public funding, and(ii) is common in large e-science projects, e.g., [17], [18],[19], [20], and in other virtual ... L = Eθ. {. i. x. [. (1 λ)ui(x|θi). λ1Fi(θi)fi(θi)θiui(x|θi).

  6. Optimal Call Routing in VoIPCostas Courcoubetis Department of…

    www.statslab.cam.ac.uk/~rrw1/publications/Courcoubetis%20-%20Kalogiros%20-%202009%20Weber%20Optimal%20call%20routing%20in%20VoIP.pdf
    15 Sep 2011: 0 1 2 3 4 5 6. 0.05. 0.10. 0.15. 0.20. ... Acknowledgement. This research project is co-financed by E.U.-European So-cial Fund (80%) and the Greek Ministry of Development-GSRT (20%).

  7. Optimal Selection of Stochastic Intervals under a Sum Constraint

    www.statslab.cam.ac.uk/~rrw1/publications/Coffman%20-%20Flatto-%20Weber%201987%20Optimal%20selection%20of%20stochastic%20intervals%20under%20a%20sum%20constraint.pdf
    15 Sep 2011: From (19) and (20). (29) P(Di n D2) = O(exp (-n n)). ... R. WEBER. 09 ---)=20. 08-. 07. 06. 09 0 t0 20 30 40 50.

  8. Stability of On-Line Bin Packing with Random Arrivals and…

    www.statslab.cam.ac.uk/~rrw1/publications/Courcoubetis%20-%20Weber%201990%20Stability%20of%20on-line%20bin%20packing%20with%20random%20arrivals%20and%20long-run%20average%20constraints.pdf
    15 Sep 2011: 3 , a , c J • • • ( J m a m c ; / 3 m 1 a m 1 c am 1 = 0, (2.20). ... 1 in (2.20) must be of equal sign, contradict-ing the assumption we made earlier.

  9. Admission control and routing in ATM networks using inferences from…

    www.statslab.cam.ac.uk/~rrw1/publications/Courcoubetis%20-%20Kesidis%20-%20Ridder%20-%20Walrand%20-Weber%201995%20Admission%20control%20and%20routing%20in%20ATM%20networks%20using%20inferences%20from%20measured%20buffer%20occupancy.pdf
    15 Sep 2011: 20 -20 l o 1. QT = [ -lo The number of sources, N , was varied. ... for Fa and (20,15,5) for Fb for both small and large-time simulations.

  10. Scheduling Jobs with Stochastic Processing Requirements on Parallel…

    www.statslab.cam.ac.uk/~rrw1/publications/Weber%201982%20Scheduling%20jobs%20with%20stochastic%20processing%20requirements%20on%20parallel%20machines%20to%20minimize%20makespan%20or%20flowtime.pdf
    15 Sep 2011: The inductive step for (16) comes from (20), using the fact that for an sc2 density,. ... 10-19]. The Saddlepoint Approximation for a General Birth Process [pp. 20-28].

  11. A Self-Organizing Bin Packing HeuristicJanos Csirik � David S. ...

    www.statslab.cam.ac.uk/~rrw1/publications/Csirik%20-%20Johnson%20-%20Kenyon%20-%20Shor%20-%20Weber%201999%20A%20self-organizing%20bin%20packing%20heuristic.pdf
    15 Sep 2011: A Self Organizing Bin Packing Heuristic 9. h. j. 0 10 20 30 40 50. ... 0. 20. 40. 60. 80. 100. -----------------------------------------------------------------. --------------------------------------------------------------. -----------------------------

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