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DAC
2004
ACM
15 years 3 months ago
A methodology to improve timing yield in the presence of process variations
The ability to control the variations in IC fabrication process is rapidly diminishing as feature sizes continue towards the sub-100 nm regime. As a result, there is an increasing...
Sreeja Raj, Sarma B. K. Vrudhula, Janet Meiling Wa...
SDM
2007
SIAM
131views Data Mining» more  SDM 2007»
15 years 1 months ago
Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach
In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
Yijian Bai, Haixun Wang, Carlo Zaniolo
BMCBI
2007
149views more  BMCBI 2007»
14 years 12 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
CORR
2006
Springer
153views Education» more  CORR 2006»
14 years 12 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
IOR
2006
91views more  IOR 2006»
14 years 11 months ago
Robust One-Period Option Hedging
The paper considers robust optimization to cope with uncertainty about the stock return process in one period option hedging problems. The robust approach relates portfolio choice ...
Frank Lutgens, Jos F. Sturm, Antoon Kolen