Results 251 to 260 of about 9,847,496 (288)

Recognition of functional dependencies in data

1993
Discovery of regularities in data involves search in many spaces, for instance in the space of functional expressions. If data do not fit any solution in a particular space, much time could be saved if that space was not searched at all. A test which determines the existence of a solution in a particular space, if available, can prevent unneeded search.
Robert Zembowicz, Jan M. Zytkow
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Data Dependence in Combining Classifiers

2003
It has been accepted that multiple classifier systems provide a platform for not only performance improvement, but more efficient and robust pattern classification systems. A variety of combining methods have been proposed in the literature and some work has focused on comparing and categorizing these approaches.
Mohamed S. Kamel, Nayer M. Wanas
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Incremental data dependence analysis

Proceedings of 3rd International Conference on High Performance Computing (HiPC), 2002
Under the existing framework for dependence analysis, every time a program is modified, exhaustive reanalysis has to be carried out to restructure the program. Often the changes in the program may be limited to a small portion. This may not affect a major part of the value based dependences.
K. V. Praveen, Sajeev Kumar Aggarwal, R. K. Ghosh   +2 more
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Engineering a data dependence test

Concurrency: Practice and Experience, 1993
AbstractMany papers have been written dealing with the science of data dependence tests, particularly for dependence of arrays in loops; the techniques typically reduce the dependence problem to an algebraic problem, then solve the algebraic problem by an algorithm which has some desired blend of efficiency, generality or precision.
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Dependence analysis for recursive data

Proceedings of the 1998 International Conference on Computer Languages (Cat. No.98CB36225), 2002
The paper describes a general and powerful method for dependence analysis in the presence of recursive data constructions. The particular analysis presented is for identifying partially dead recursive data, but the general framework for representing and manipulating recursive substructures applies to all dependence analyses. The method uses projections
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Fuzzing with Data Dependency Information

2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P), 2022
Alessandro Mantovani, Andrea Fioraldi, Davide Balzarotti   +2 more
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Multivariate sensitivity analysis and derivative-based global sensitivity measures with dependent variables

Reliability Engineering and System Safety, 2021
Sergei Kucherenko
exaly  

Recent Advances in the Role of Autophagy in Endocrine-Dependent Tumors

Endocrine Reviews, 2023
Anvita Komarla, Suzanne Dufresne, Christina G Towers   +2 more
exaly  

Color‐Tunable, Excitation‐Dependent, and Time‐Dependent Afterglows from Pure Organic Amorphous Polymers

Advanced Materials, 2020
Tianwen Zhu, Yueying Lai, Kunyan Sui
exaly  

Data dependences as abstract interpretations

1997
The power of any parallelizing compiler is limited by its program analyzers. Finding the right abstraction for program analysis is crucial. The various existing data dependence abstractions can be viewed simply as approximations of the others. Moreover, data dependences have common structures, which can be exhibited by "abstraction of the structure of ...
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