On the complexity analysis of randomized block-coordinate descent methods
نویسندگان
چکیده
منابع مشابه
On the Complexity Analysis of Randomized Block-Coordinate Descent Methods
In this paper we analyze the randomized block-coordinate descent (RBCD) methods proposed in [11, 15] for minimizing the sum of a smooth convex function and a blockseparable convex function, and derive improved bounds on their convergence rates. In particular, we extend Nesterov’s technique developed in [11] for analyzing the RBCD method for minimizing a smooth convex function over a block-separ...
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In this paper we develop a randomized block-coordinate descent method for minimizing the sum of a smooth and a simple nonsmooth block-separable convex function and prove that it obtains an ε-accurate solution with probability at least 1− ρ in at most O((n/ε) log(1/ρ)) iterations, where n is the number of blocks. This extends recent results of Nesterov [Efficiency of coordinate descent methods o...
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In this paper we study smooth convex programming problems where the decision variables vector is split into several blocks of variables. We analyze the block coordinate gradient projection method in which each iteration consists of performing a gradient projection step with respect to a certain block taken in a cyclic order. Global sublinear rate of convergence of this method is established and...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2014
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-014-0800-2