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» A Guided Monte Carlo Approach to Optimization Problems
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IOR
2011
107views more  IOR 2011»
14 years 5 months ago
Information Collection on a Graph
We derive a knowledge gradient policy for an optimal learning problem on a graph, in which we use sequential measurements to refine Bayesian estimates of individual edge values i...
Ilya O. Ryzhov, Warren B. Powell
GECCO
2008
Springer
131views Optimization» more  GECCO 2008»
14 years 11 months ago
A new memetic strategy for the numerical treatment of multi-objective optimization problems
In this paper we propose a novel iterative search procedure for multi-objective optimization problems. The iteration process – though derivative free – utilizes the geometry o...
Oliver Schütze, Gustavo Sanchez, Carlos A. Co...
ICPR
2008
IEEE
15 years 4 months ago
Approximation of salient contours in cluttered scenes
This paper proposes a new approach to describe the salient contours in cluttered scenes. No need to do the preprocessing, such as edge detection, we directly use a set of random s...
Rui Huang, Nong Sang, Qiling Tang
TCAD
2008
136views more  TCAD 2008»
14 years 10 months ago
A Geometric Programming-Based Worst Case Gate Sizing Method Incorporating Spatial Correlation
We present an efficient optimization scheme for gate sizing in the presence of process variations. Our method is a worst-case design scheme, but it reduces the pessimism involved i...
Jaskirat Singh, Zhi-Quan Luo, Sachin S. Sapatnekar
AAAI
1994
14 years 11 months ago
Activity Analysis: The Qualitative Analysis of Stationary Points for Optimal Reasoning
We present a theory of a modeler's problem decomposition skills in the context of optimal reasonzng -- the use of qualitative modeling to strategically guide numerical explor...
Brian C. Williams, Jonathan Cagan