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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.

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 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.

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

15 Apr 2010: Stigler's guess for the optimal solution was off by only 24 cents per year.

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

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.

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.

28 Apr 2010: j=31. xij 1,. 14. j=11. xij 26. j=24. xij 1,. 30. ... 36.1FI 31.2FF 27.7HA 22.6HC 38.6MS 12.5MI 73.7BS. 51.7PI 18.6OJ 29.7QP 4.0GS 24.6SM 30.4SE 5.7TK = CARB;.