scholarly journals Gradient-based method with active set strategy for $\ell _1$ optimization

2017 ◽  
Vol 87 (311) ◽  
pp. 1283-1305 ◽  
Author(s):  
Wanyou Cheng ◽  
Yu-Hong Dai
Keyword(s):  
Active Set ◽  
Active Set Strategy ◽  
Gradient Based

Active set strategy of optimized extreme learning machine

2014 ◽  
Vol 59 (31) ◽  
pp. 4152-4160 ◽  
Author(s):  
Xiao-Jian Ding ◽  
Bao-Fang Chang
Keyword(s):  
Extreme Learning Machine ◽  
Active Set ◽  
Active Set Strategy ◽  
Learning Machine

Implementation of Semi-Heuristic Reasoning for Boundedness Analysis of Design Optimization Models

1987 ◽  
Author(s):  
J. R. J. Rao ◽  
P. Y. Papalambros
Keyword(s):  
Optimal Design ◽  
Heuristic Search ◽  
Optimization Models ◽  
Programming Environment ◽  
Initial Model ◽  
Active Set ◽  
Design Models ◽  
Active Set Strategy ◽  
Reasoning System ◽  
Global Boundedness

Abstract A production system performing global boundedness analysis of optimal design models has been implemented in the OPS5 programming environment. The system receives as input an initial model monotonicity table and derives global facts about boundedness and constraint activity using monotonicity principles. Additional facts may be discovered by heuristic search of implicit elimination sequences that examine boundedness of reduced models with active constraints eliminated. The global facts generated automatically by this reasoning system can be used either for a global solution, or for a combined local-global active set strategy.

PRIMA: A Production-Based Implicit Elimination System for Monotonicity Analysis of Optimal Design Models

1991 ◽  
Vol 113 (4) ◽  
pp. 408-415 ◽  
Author(s):  
J. R. Rao ◽  
P. Y. Papalambros
Keyword(s):  
Optimal Design ◽  
Heuristic Search ◽  
Programming Environment ◽  
Initial Model ◽  
Active Set ◽  
Design Models ◽  
Active Set Strategy ◽  
Knowledge Based ◽  
Reasoning System ◽  
Monotonicity Analysis

Monotonicity analysis is a useful method for analyzing optimal design models prior to numerical computation. Much of the information required for such analysis is represented in the monotonicity table. Rigorous procedures using the monotonicity principles and the implicit function theorem have been combined with heuristics, to extract additional constraint activity knowledge based only on the information contained in the monotonicity table. PRIMA is a production system implemented in the OPS5 programming environment. The system receives as input the monotonicity table of the initial model and derives global facts about boundedness and constraint activity by heuristic search of sequences of successively reduced models. Such reduction is obtained by implicit elimination of active constraints. Global facts generated automatically by this reasoning system can be used either for a global solution, or for a combined local-global active set strategy.

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