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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 4 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
142
Voted
CCE
2004
15 years 4 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»
15 years 11 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
MSR
2006
ACM
15 years 11 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...
150
Voted
SIGIR
2008
ACM
15 years 5 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