Multi-stage Learning of Linear Algebra Algorithms

被引：0

作者：

Eijkhout, Victor ^{[1
]}

Fuentes, Erika ^{[2
,3
]}

机构：

[1] Univ Texas Austin, Texas Adv Comp Ctr, Austin, TX 78712 USA

[2] Univ Tennessee, Innovat Comp Lab, Knoxville, TN 37996 USA

[3] Microsoft Res, Cambridge CB12FB, England

来源：

SEVENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/ICMLA.2008.10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In evolving applications, there is a need for the dynamic selection of algorithms or algorithm parameters. Such selection is hardly ever governed by exact theory, so intelligent recommender systems have been proposed In our application area, the iterative solution of linear systems of equations, the recommendation process is especially complicated, since the classes have a multi-dimensional structure. We discuss different strategies of recommending the different components of the algorithms.

引用

页码：402 / +

页数：2

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