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» High-Level Optimization via Automated Statistical Modeling
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GECCO
2008
Springer
154views Optimization» more  GECCO 2008»
13 years 8 months ago
Automated shape composition based on cell biology and distributed genetic programming
Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell i...
Linge Bai, Manolya Eyiyurekli, David E. Breen
EMNLP
2008
13 years 9 months ago
Lattice-based Minimum Error Rate Training for Statistical Machine Translation
Minimum Error Rate Training (MERT) is an effective means to estimate the feature function weights of a linear model such that an automated evaluation criterion for measuring syste...
Wolfgang Macherey, Franz Josef Och, Ignacio Thayer...
GECCO
2003
Springer
120views Optimization» more  GECCO 2003»
14 years 26 days ago
System-Level Synthesis of MEMS via Genetic Programming and Bond Graphs
Initial results have been achieved for automatic synthesis of MEMS system-level lumped parameter models using genetic programming and bond graphs. This paper first discusses the ne...
Zhun Fan, Kisung Seo, Jianjun Hu, Ronald C. Rosenb...
MSR
2010
ACM
13 years 9 months ago
Identifying security bug reports via text mining: An industrial case study
-- A bug-tracking system such as Bugzilla contains bug reports (BRs) collected from various sources such as development teams, testing teams, and end users. When bug reporters subm...
Michael Gegick, Pete Rotella, Tao Xie
ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson