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PPSN
2000
Springer
13 years 11 months ago
Optimizing through Co-evolutionary Avalanches
Abstract. We explore a new general-purpose heuristic for nding highquality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-or...
Stefan Boettcher, Allon G. Percus, Michelangelo Gr...
IWANN
1999
Springer
13 years 11 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
DFT
2003
IEEE
64views VLSI» more  DFT 2003»
14 years 24 days ago
Hybrid BIST Time Minimization for Core-Based Systems with STUMPS Architecture
1 This paper presents a solution to the test time minimization problem for core-based systems that contain sequential cores with STUMPS architecture. We assume a hybrid BIST approa...
Gert Jervan, Petru Eles, Zebo Peng, Raimund Ubar, ...
CORR
2010
Springer
151views Education» more  CORR 2010»
13 years 4 months ago
Selective Call Out and Real Time Bidding
Display ads on the Internet are increasingly sold via ad exchanges such as RightMedia, AdECN and Doubleclick Ad Exchange. These exchanges allow real-time bidding, that is, each ti...
Tanmoy Chakraborty, Eyal Even-Dar, Sudipto Guha, Y...
FOCS
1995
IEEE
13 years 11 months ago
Disjoint Paths in Densely Embedded Graphs
We consider the following maximum disjoint paths problem (mdpp). We are given a large network, and pairs of nodes that wish to communicate over paths through the network — the g...
Jon M. Kleinberg, Éva Tardos