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ICTAI
1997
IEEE
15 years 8 months ago
Exploiting Symbolic Techniques within Genetic Algorithms for Power Optimization
This paper proposes an optimization algorithm for reducing the power dissipation in a sequential circuit. The encoding of the different states in a Finite State Machine is modifie...
S. Chuisano, Fulvio Corno, Paolo Prinetto, Maurizi...
161
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ICCAD
1995
IEEE
90views Hardware» more  ICCAD 1995»
15 years 8 months ago
An optimal algorithm for area minimization of slicing floorplans
The traditional algorithm of Stockmeyer for area minimization of slicing oorplans has time (and space) complexity O(n2 ) in the worst case, or O(nlogn) for balanced slicing. For ...
Weiping Shi
APPROX
2005
Springer
136views Algorithms» more  APPROX 2005»
15 years 10 months ago
What About Wednesday? Approximation Algorithms for Multistage Stochastic Optimization
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Anupam Gupta, Martin Pál, R. Ravi, Amitabh ...
IJCAI
2001
15 years 6 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
CEC
2009
IEEE
15 years 11 months ago
Gradient estimation in global optimization algorithms
Abstract— The role of gradient estimation in global optimization is investigated. The concept of a regional gradient is introduced as a tool for analyzing and comparing different...
Megan Hazen, Maya R. Gupta