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219,291
Asymptotic Convergence of DegreeRaising
"... It is well known that the degreeraised BernsteinBézier coefficients of degree n of a polynomial g converge to g at the rate 1/n. In this paper we consider the polynomial An(g) of degree ≤ n interpolating the coefficients. We show how An can be viewed as an inverse to the Bernstein polynomial opera ..."
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operator and that the derivatives An(g) (r) converge uniformly to g (r) at the rate 1/n for all r. We also give an asymptotic expansion of Voronovskaya type for An(g) and discuss some shape preserving properties of this polynomial.
ON ASYMPTOTIC CONVERGENCE OF NONSYMMETRIC JACOBI ALGORITHMS
"... Abstract. The asymptotic convergence behavior of cyclic versions of the nonsymmetric Jacobi algorithm for the computation of the Schur form of a general complex matrix is investigated. Similar to the symmetric case, the nonsymmetric Jacobi algorithm proceeds by applying a sequence of rotations that ..."
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Cited by 3 (1 self)
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Abstract. The asymptotic convergence behavior of cyclic versions of the nonsymmetric Jacobi algorithm for the computation of the Schur form of a general complex matrix is investigated. Similar to the symmetric case, the nonsymmetric Jacobi algorithm proceeds by applying a sequence of rotations
Asymptotic Convergence of an SMO Algorithm without Any Assumptions
 IEEE TRANSACTIONS ON NEURAL NETWORKS
, 2002
"... The asymptotic convergence in Lin [6] can be applied to a modified SMO algorithm by Keerthi et al. [5] with some assumptions. Here we show that for this algorithm those assumptions are not necessary. ..."
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Cited by 23 (4 self)
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The asymptotic convergence in Lin [6] can be applied to a modified SMO algorithm by Keerthi et al. [5] with some assumptions. Here we show that for this algorithm those assumptions are not necessary.
The Asymptotic ConvergenceRate of Qlearning
, 1998
"... In this paper we show that for discounted MDPs with discount factor fl ? 1=2 the asymptotic rate of convergence of Qlearning is O(1=t R(1\Gammafl) ) if R(1 \Gamma fl) ! 1=2 and O( p log log t=t) otherwise provided that the stateaction pairs are sampled from a fixed probability distribution. He ..."
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Cited by 21 (3 self)
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In this paper we show that for discounted MDPs with discount factor fl ? 1=2 the asymptotic rate of convergence of Qlearning is O(1=t R(1\Gammafl) ) if R(1 \Gamma fl) ! 1=2 and O( p log log t=t) otherwise provided that the stateaction pairs are sampled from a fixed probability distribution
The Asymptotic ConvergenceRate of QIearning
"... szepes((trnath.uszeged.hu In this paper we show that for discounted MDPs with discount factor ' (> 1/2 the asymptotic rate of convergence of Qlearning is O(I/tR(lO)) if R(1 ':I) < 1/2 and O ( Jlog log t/t) otherwise provided that the stateaction pairs are sampled from a fixed pr ..."
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szepes((trnath.uszeged.hu In this paper we show that for discounted MDPs with discount factor ' (> 1/2 the asymptotic rate of convergence of Qlearning is O(I/tR(lO)) if R(1 ':I) < 1/2 and O ( Jlog log t/t) otherwise provided that the stateaction pairs are sampled from a fixed
On the Asymptotic Convergence Properties of Turbo Codes
"... In this paper we present an analysis of the convergence properties of turbo codes at high signaltonoise ratio (SNR). We introduce a simple nonlinear model based on the weight enumerator of the constituent codes to describe the iterates of the biterrorrate (BER). Then, we characterize the dynamic ..."
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In this paper we present an analysis of the convergence properties of turbo codes at high signaltonoise ratio (SNR). We introduce a simple nonlinear model based on the weight enumerator of the constituent codes to describe the iterates of the biterrorrate (BER). Then, we characterize
DARKHALO CUSP: ASYMPTOTIC CONVERGENCE
, 2002
"... We propose a model for how the buildup of dark halos by merging satellites produces an inner cusp, of a density profile ρ ∝ r −αin with αin → αas> ∼ 1, as seen in cosmological Nbody simulations. Dekel & Devor (2002) showed that a core of αin < 1 exerts tidal compression which prevents loc ..."
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by toy simulations, shows that a sequence of cosmological mergers with homologous satellites slowly leads to a fixedpoint asymptotic cusp with a slope αas> 1. The cusp depends only weakly on the power spectrum of fluctuations, in agreement with cosmological Nbody simulations. During a long interim
Asymptotic convergence of constrained primaldual dynamics
, 2015
"... This paper studies the asymptotic convergence properties of the primaldual dynamics designed for solving constrained concave optimization problems using classical notions from stability analysis. We motivate the need for this study by providing an example that rules out the possibility of employin ..."
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This paper studies the asymptotic convergence properties of the primaldual dynamics designed for solving constrained concave optimization problems using classical notions from stability analysis. We motivate the need for this study by providing an example that rules out the possibility
Asymptotic Convergence Analysis of the Proximal Point Algorithm
 SIAM Journal on Control and Optimization
, 1984
"... The asymptotic convergence of the proximal point algorithm (PPA), for the solution of equations of type 0 e Tz, where T is a multivalued maximal monotone operator in a real Hilbert space is analyzed. When 0 e Tz has a nonempty solution set Z, convergence rates are shown to depend on how rapidly T gr ..."
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Cited by 37 (0 self)
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The asymptotic convergence of the proximal point algorithm (PPA), for the solution of equations of type 0 e Tz, where T is a multivalued maximal monotone operator in a real Hilbert space is analyzed. When 0 e Tz has a nonempty solution set Z, convergence rates are shown to depend on how rapidly
Results 1  10
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219,291