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27 Apr 2010: First cut constraint. Second cut constraint. Product form. Outline. Slide Number 24.

20 Jul 2010: 151.51 30.24 24.68 4.08 58.63 69.7 24.57 43.02 12.19 20.11 39.46 73.8 35.04 30.05 29.97 ... 29.96 24.24 4.17 58.27 68.57 24.42 42.2 12.24 19.88 36.65 73.43 34.77 29.87 29.6 28.33

9 Feb 2010: Recall from [23, 24] that hc(β) > 0 if and only if β < βc. ... 8.25). Inequality (8.24) holds by the positive association of random-cluster measureswith cluster-weights at least 1.

19 Nov 2010: F. Combining the bounds completes the proof of (24).It remains to prove (25). ... By (19) and (27), we have V ′ c2(λ)nσ 2, and the condition on t together with (24) givesthe result.

24 Mar 2010: n = 100 n = 200 n = 500 n = 1000 n = 2000d = 2 1.5 secs (260) 2.9 secs (500) 50 secs (1270) 4 mins (2540) 24 mins (5370)d = 3 6

10 Nov 2010: 23. 4.2.2 Notation. 24. 4.2.3 Defining the rates of individual interactions. ... 24. 4.2.4 Deriving the Markov chain rates. 25. 4.2.5 Example: n = 1.

25 Nov 2010: 236.5 Calculation of the Gittins index. 24. 6.6 Forward induction policies. ... 24. 7 Average-cost Programming 257.1 Average-cost optimization. 257.2 Example: admission control at a queue.

14 Feb 2010: the queue size. Instead, as described in [24, 25], protocols act to control the. ... Computer Communication Review, 38 (2008) 51–. 62. [24] G. Raina, D.

17 Aug 2010: F. Sidorenko, Percolation theoryand some applications, Itogi Nauki i Techniki (Series of Probability Theory,Mathematical Statistics, Theoretical Cybernetics) 24 (1986), 53–110.

26 Feb 2010: 24) ch(p, q) ‖p q‖2,λ Ch(p, q). holds for p, q P (t, ζ, D) with t > 1/2 and ζ > 0 (cf. ... Consequently, us-ing (24), the Hellinger-bracketing metric entropy H[](ε, P̄H(n), ‖ ‖2,λ) (with P̄H(n) ={ p : p P̃H(n) }) can be bounded by the L2(T

20 Jul 2010: 9.42. 55.88. 71.47. 25.74. 71.76. 16.87. 24. 66.91. 83.13. 34.2. 36. ... 13.31. 208.99. 33.94. 31.57. 8.21. 56.9. 69.16. 25. 64. 16.71. 24.39.

24 Feb 2010: incentives are provided to the larger system [24, 38]. Might some of these ideas transfer to help our understanding of the. ... of rate control algorithms in the Internet [24, 38]. Let I+(n) = {i I : ni > 0}.

19 Feb 2010: The Annals of Statistics2010, Vol. 38, No. 2, 1122–1170DOI: 10.1214/09-AOS738 Institute of Mathematical Statistics, 2010. CONFIDENCE BANDS IN DENSITY ESTIMATION. BY EVARIST GINÉ AND RICHARD NICKL. University of Connecticut and University of