Results 21 to 30 of about 268,699 (268)
Rate of Convergence of the Bundle Method [PDF]
Journal of Optimization Theory and Applications, 2017 We prove that the bundle method for nonsmooth optimization achieves solution accuracy $\varepsilon$ in at most $\mathcal{O}\big(\ln(1/\varepsilon)/\varepsilon\big)$ iterations, if the function is strongly convex. The result is true for the versions of the method with multiple cuts and with cut aggregation.
Yu Du 0003, Andrzej Ruszczynski
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Convergence Rates for Markov Chains [PDF]
SIAM Review, 1995 Summary: This is an expository paper that presents various ideas related to nonasymptotic rates of convergence for Markov chains. Such rates are of great importance for stochastic algorithms that are widely used in statistics and in computer science. They also have applications to analysis of card shuffling and other areas.
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On the Convergence Rate of the Chaos Game [PDF]
International Mathematics Research Notices, 2022 Abstract This paper studies how long it takes the orbit of the chaos game to reach a certain density inside the attractor of a strictly contracting IFS of which we only assume that its lower dimension is positive. We show that the rate of growth of this cover time is determined by the Minkowski dimension of the push-forward of the shift ...
Bárány, Balázs +2 more
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On the convergence rates of asynchronous iterations
53rd IEEE Conference on Decision and Control, 2014 This paper presents a unifying convergence result for asynchronous iterations involving pseudo-contractions in the block-maximum norm. Contrary to previous results which only established asymptotic convergence or studied simplified models of asynchronism, our result allows to bound the convergence rates for both partially and totally asynchronous ...
Feyzmahdavian, Hamid Reza +1 more
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Communications, 2023 Adaptive algorithms are used in updating the filter coefficients for active noise cancellation applications in reduction of vehicle cabin noise. The performance of the adaptive algorithms in low-frequency noise cancellation depends on how efficiently it ...
Janak Kapoor +3 more
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Convergence Rates for Generalized Descents [PDF]
The Electronic Journal of Combinatorics, 2011 d-descents are permutation statistics that generalize the notions of descents and inversions. It is known that the distribution of d-descents 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 statistics and obtain bounds on the rate of convergence using
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Open Mathematics, 2023 This article presents an approximation of discrete Markov decision processes with small noise on Borel spaces with an infinite horizon and an expected total discounted cost by the corresponding deterministic Markov process.
Portillo-Ramírez Gustavo +3 more
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On the Rate of Convergence of Greedy Algorithms
Mathematics, 2023 In this paper, a new criterion for the evaluation of the theoretical efficiency of a greedy algorithm is suggested. Using this criterion, we prove some results on the rate of convergence of greedy algorithms, which provide expansions. We consider both the case of Hilbert spaces and the more general case of Banach spaces. The new component of this paper
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On Convergence Rate of MRetrace
MathematicsOff-policy is a key setting for reinforcement learning algorithms. In recent years, the stability of off-policy learning for value-based reinforcement learning has been guaranteed even when combined with linear function approximation and bootstrapping ...
Xingguo Chen +4 more
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Rate of convergence of Lawson’s algorithm [PDF]
Mathematics of Computation, 1972 The algorithm of Charles L. Lawson determines uniform approximations of functions as limits of weighted L 2
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