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BMCBI
2006
165views more  BMCBI 2006»
13 years 8 months ago
Improved variance estimation of classification performance via reduction of bias caused by small sample size
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
Ulrika Wickenberg-Bolin, Hanna Göransson, M&a...
WSC
1997
13 years 9 months ago
The Impact of Transients on Simulation Variance Estimators
Given a stationary simulation process with unknown mean µ , interest frequently lies in, and various methods exist for, developing estimates and confidence intervals for µ . Typ...
Daniel H. Ockerman, David Goldsman
ALT
2008
Springer
14 years 5 months ago
Active Learning in Multi-armed Bandits
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...
András Antos, Varun Grover, Csaba Szepesv&a...
TCAD
2010
164views more  TCAD 2010»
13 years 3 months ago
Advanced Variance Reduction and Sampling Techniques for Efficient Statistical Timing Analysis
The Monte-Carlo (MC) technique is a traditional solution for a reliable statistical analysis, and in contrast to probabilistic methods, it can account for any complicate model. How...
Javid Jaffari, Mohab Anis
WSC
2007
13 years 10 months ago
Confidence interval estimation using linear combinations of overlapping variance estimators
We develop new confidence-interval estimators for the mean and variance parameter of a steady-state simulation output process. These confidence intervals are based on optimal li...
Tûba Aktaran-Kalayci, David Goldsman, James ...