Int. J. of Intelligent Engineering Informatics, Vol. x, No. x, 1–26 Numerical Program Optimization by Automatic Improvement of the Accuracy of Computations Nasrine Damouche* and Matthieu Martel Universit´e de Perpign

Source URL: perso.univ-perp.fr

• Functions and mappings
• Mathematical analysis
• Mathematics
• Computer arithmetic
• Limit of a function
• Abstract interpretation
• Unit in the last place
• Exponentiation
• Integral
• Lambda calculus
• Quantifier
• Combinatory logic

This paper was presented as part of the main technical program at IEEE INFOCOMFeasibility and Optimization of Delay Guarantees for Non-homogeneous Flows in IEEEWLANs Yan Gao∗ , Chee Wei Tan† , Ying Hua

Source URL: www.cs.cityu.edu.hk

SUPPLY CHAIN OPTIMIZATION PROGRAM OVERVIEW Reducing risk. Increasing visibility. Building stronger manufacturers. The MEP Supply Chain optimization program is a strategic approach to solving the challenges of U.S. manufa

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Manuel Hermenegildo Areas of Interest Energy-Aware Computing, Resource / non-functional property analysis, verification, and control; Global Program Analysis, Optimization, Verification, Debugging; Abstract Interpretatio

Source URL: cliplab.org

Integrated Program Debugging, Verification, and Optimization Using Abstract Interpretation (and The Ciao System Preprocessor) Manuel V. Hermenegildo a,b Germ´an Puebla a Francisco Bueno a Pedro L´opez-Garc´ıa a

Source URL: cliplab.org

1st International Workshop on Dynamic Compilation for Architectural Heterogeneity and Program Optimization Austin, TX – February 4, 2017 Held in conjunction with the International Symposium on Code Generation and Optim

Source URL: dcahpo.files.wordpress.com

A UNIFIED APPROACH TO GLOBAL PROGRAM OPTIMIZATION Gary A.

Source URL: drona.csa.iisc.ernet.in

Manuel Hermenegildo Areas of Interest Advanced Program Development Technology, Global Program Analysis / Optimization / Verification, Abstract Interpretation, Abstract Machines, Parallelizing Compilers, Resource-Aware Di

Source URL: cliplab.org

Program Optimization for Faster Genetic Programming∗ Bradley J. Lucier Sudhakar Mamillapalli Jens Palsberg

Source URL: www.math.purdue.edu