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» An Approach to use Executable Models for Testing
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ML
2002
ACM
114views Machine Learning» more  ML 2002»
15 years 6 months ago
Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts
The execution order of a block of computer instructions on a pipelined machine can make a difference in running time by a factor of two or more. Compilers use heuristic schedulers...
Amy McGovern, J. Eliot B. Moss, Andrew G. Barto
CCE
2004
15 years 7 months ago
Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
José María Ponce-Ortega, Vicente Ric...
FSKD
2007
Springer
193views Fuzzy Logic» more  FSKD 2007»
16 years 1 months ago
Panoramic Background Model under Free Moving Camera
segmentation of moving regions in outdoor environment under a moving camera is a fundamental step in many vision systems including automated visual surveillance, human-machine int...
Naveed I. Rao, Huijun Di, Guangyou Xu
202
Voted
MSR
2006
ACM
16 years 1 months ago
Detecting similar Java classes using tree algorithms
Similarity analysis of source code is helpful during development to provide, for instance, better support for code reuse. Consider a development environment that analyzes code whi...
Tobias Sager, Abraham Bernstein, Martin Pinzger, C...
SIGIR
2008
ACM
15 years 7 months ago
A study of learning a merge model for multilingual information retrieval
This paper proposes a learning approach for the merging process in multilingual information retrieval (MLIR). To conduct the learning approach, we also present a large number of f...
Ming-Feng Tsai, Yu-Ting Wang, Hsin-Hsi Chen