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Convergence rates of cascade algorithms
 Proc. Amer. Math. Soc
, 2001
"... We consider solutions of a refinement equation written in the form as φ = � α ∈ Z s a(α)φ(M · − α), where a is a finitely supported sequence called the refinement mask. Associated with the mask a is a linear operator Qa defined on Lp(IR s) by Qaψ: = � α ∈ Zs a(α)ψ(M · − α). This paper is concerned ..."
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Cited by 4 (3 self)
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is concerned with the convergence of the cascade algorithm associated with a, i.e., the convergence of the sequence (Qn aψ)n=1,2,... in the Lpnorm. Our main result gives estimates for the convergence rate of the cascade algorithm. Let φ be the normalized solution of the above refinement equation
Optimization Flow Control, I: Basic Algorithm and Convergence
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 1999
"... We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm. In thi ..."
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Cited by 690 (64 self)
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We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm
Convergence rates for posterior distributions and adaptive
, 2004
"... The goal of this paper is to provide theorems on convergence rates of posterior distributions that can be applied to obtain good convergence rates in the context of density estimation as well as regression. We show how to choose priors so that the posterior distributions converge at the optimal rate ..."
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Cited by 25 (0 self)
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The goal of this paper is to provide theorems on convergence rates of posterior distributions that can be applied to obtain good convergence rates in the context of density estimation as well as regression. We show how to choose priors so that the posterior distributions converge at the optimal
The Convergence Rate of AdaBoost
"... Abstract. We pose the problem of determining the rate of convergence at which AdaBoost minimizes exponential loss. Boosting is the problem of combining many “weak, ” higherror hypotheses to generate a single “strong” hypothesis with very low error. The AdaBoost algorithm of Freund and Schapire (199 ..."
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Cited by 9 (3 self)
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Abstract. We pose the problem of determining the rate of convergence at which AdaBoost minimizes exponential loss. Boosting is the problem of combining many “weak, ” higherror hypotheses to generate a single “strong” hypothesis with very low error. The AdaBoost algorithm of Freund and Schapire
Convergence rates of Approximation by Translates
 AI Memo 1288 (AI Laboratory, MIT
, 1995
"... In this paper we consider the problem of approximating a function belonging to some function space \Phi by a linear combination of n translates of a given function G. ..."
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Cited by 10 (0 self)
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In this paper we consider the problem of approximating a function belonging to some function space \Phi by a linear combination of n translates of a given function G.
The Convergence Rate Of Godunov Type Schemes
, 1994
"... . Godunov type schemes form a special class of transport projection methods for the approximate solution of nonlinear hyperbolic conservation laws. We study the convergence rate of such schemes in the context of scalar conservation laws. We show how the question of consistency for Godunov type schem ..."
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Cited by 15 (7 self)
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. Godunov type schemes form a special class of transport projection methods for the approximate solution of nonlinear hyperbolic conservation laws. We study the convergence rate of such schemes in the context of scalar conservation laws. We show how the question of consistency for Godunov type
Convergence Rates for Generalized Descents
"... ddescents are permutation statistics that generalize the notions of descents and inversions. It is known that the distribution of ddescents of permutations of length n satisfies a central limit theorem as n goes to infinity. We provide an explicit formula for the mean and variance of these statist ..."
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of these statistics and obtain bounds on the rate of convergence using Stein’s method. 1
Reopening the Convergence Debate: A new look at crosscountry growth empirics
 JOURNAL OF ECONOMIC GROWTH
, 1996
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