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» The Semantics of Future and Its Use in Program Optimizations
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TSMC
2008
140views more  TSMC 2008»
14 years 9 months ago
Adaptive Feedback Control by Constrained Approximate Dynamic Programming
A constrained approximate dynamic programming (ADP) approach is presented for designing adaptive neural network (NN) controllers with closed-loop stability and performance guarante...
S. Ferrari, J. E. Steck, R. Chandramohan
COCOA
2007
Springer
15 years 4 months ago
A New Dynamic Programming Algorithm for Multiple Sequence Alignment
Abstract. Multiple sequence alignment (MSA) is one of the most basic and central tasks for many studies in modern biology. In this paper, we present a new progressive alignment alg...
Jean-Michel Richer, Vincent Derrien, Jin-Kao Hao
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
15 years 3 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
CORR
2010
Springer
88views Education» more  CORR 2010»
14 years 10 months ago
Grothendieck inequalities for semidefinite programs with rank constraint
Grothendieck inequalities are fundamental inequalities which are frequently used in many areas of mathematics and computer science. They can be interpreted as upper bounds for the ...
Jop Briët, Fernando Mário de Oliveira ...
AAAI
1997
14 years 11 months ago
From MiniMax to Manhattan
The thinking process for playing chess by computer is significantly different from that used by humans. Although computer hardware and software have evolved considerably, computer...
T. Anthony Marsland, Yngvi Björnsson