Inexact Coordinate Descent: Complexity and Preconditioning

被引:29
作者
Tappenden, Rachael [1 ]
Richtarik, Peter [1 ]
Gondzio, Jacek [1 ]
机构
[1] Univ Edinburgh, Sch Math, Edinburgh EH9 3JZ, Midlothian, Scotland
基金
英国工程与自然科学研究理事会;
关键词
Inexact methods; Block coordinate descent; Convex optimization; Iteration complexity; Preconditioning; Conjugate gradients; GRADIENT PROJECTION; CONVERGENCE; ALGORITHM;
D O I
10.1007/s10957-016-0867-4
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
One of the key steps at each iteration of a randomized block coordinate descent method consists in determining the update to a block of variables. Existing algorithms assume that in order to compute the update, a particular subproblem is solved exactly. In this work, we relax this requirement and allow for the subproblem to be solved inexactly, leading to an inexact block coordinate descent method. Our approach incorporates the best known results for exact updates as a special case. Moreover, these theoretical guarantees are complemented by practical considerations: the use of iterative techniques to determine the update and the use of preconditioning for further acceleration.
引用
收藏
页码:144 / 176
页数:33
相关论文
共 43 条
[21]   Randomized Methods for Linear Constraints: Convergence Rates and Conditioning [J].
Leventhal, D. ;
Lewis, A. S. .
MATHEMATICS OF OPERATIONS RESEARCH, 2010, 35 (03) :641-654
[22]  
Machart P., 2012, HAL00771722
[23]  
Necoara I., 2013, ARXIV13023129V1MATHO
[24]   A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints [J].
Necoara, Ion ;
Patrascu, Andrei .
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2014, 57 (02) :307-337
[25]   Paved with good intentions: Analysis of a randomized block Kaczmarz method [J].
Needell, Deanna ;
Tropp, Joel A. .
LINEAR ALGEBRA AND ITS APPLICATIONS, 2014, 441 :199-221
[26]   Gradient methods for minimizing composite functions [J].
Nesterov, Yu .
MATHEMATICAL PROGRAMMING, 2013, 140 (01) :125-161
[27]   EFFICIENCY OF COORDINATE DESCENT METHODS ON HUGE-SCALE OPTIMIZATION PROBLEMS [J].
Nesterov, Yu .
SIAM JOURNAL ON OPTIMIZATION, 2012, 22 (02) :341-362
[28]   Efficient block-coordinate descent algorithms for the Group Lasso [J].
Qin Z. ;
Scheinberg K. ;
Goldfarb D. .
Qin, Z. (zq2107@columbia.edu), 2013, Springer Verlag (05) :143-169
[29]   Parallel stochastic gradient algorithms for large-scale matrix completion [J].
Recht B. ;
Ré C. .
Mathematical Programming Computation, 2013, 5 (2) :201-226
[30]  
Richtarik P., 2011, 4 WORKSH SIGN PROC A