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» Interval Methods: An Introduction
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ANNES
1995
14 years 17 days ago
The Development of Holte's 1R Classifier
The 1R procedure for machine learning is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the metho...
Craig G. Nevill-Manning, Geoffrey Holmes, Ian H. W...
DAGSTUHL
2008
13 years 10 months ago
Error Bounds for Lanczos Approximations of Rational Functions of Matrices
Abstract. Having good estimates or even bounds for the error in computing approximations to expressions of the form f(A)v is very important in practical applications. In this paper...
Andreas Frommer, Valeria Simoncini
MASCOTS
2007
13 years 10 months ago
Adaptive Sampling for Efficient MPSoC Architecture Simulation
—Modern micro-architecture simulators are many orders of magnitude slower than the hardware they simulate. The use of multiprocessor architectures for supporting future mobile an...
Melhem Tawk, Khaled Z. Ibrahim, Smaïl Niar
ICAD
2004
13 years 10 months ago
Aural Maps, Neural Futures
If the mental objects of philosophy, art, and science ... have a place it will be in the deepest synaptic fissures, in the hiatuses, intervals, and mean-times of the non-objectifi...
Meredith Walsh
WSC
2004
13 years 10 months ago
Permuted Weighted Area Estimators
Calvin and Nakayama previously introduced permuting as a way of improving existing standardized time series methods. The basic idea is to split a simulated sample path into nonove...
James M. Calvin, Marvin K. Nakayama