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» Using common random numbers for indifference-zone selection
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ICPR
2000
IEEE
14 years 8 months ago
Measuring the Complexity of Classification Problems
We studied a number of measures that characterize the difficulty of a classification problem. We compared a set of real world problems to random combinations of points in this mea...
Tin Kam Ho, Mitra Basu
SIAMSC
2010
134views more  SIAMSC 2010»
13 years 6 months ago
Moving Least Squares via Orthogonal Polynomials
A method for moving least squares interpolation and differentiation is presented in the framework of orthogonal polynomials on discrete points. This yields a robust and efficient ...
Michael Carley
EKAW
2000
Springer
13 years 11 months ago
Informed Selection of Training Examples for Knowledge Refinement
Knowledge refinement tools rely on a representative set of training examples to identify and repair faults in a knowledge based system (KBS). In real environments it is often diffi...
Nirmalie Wiratunga, Susan Craw
EDBT
2010
ACM
132views Database» more  EDBT 2010»
13 years 11 months ago
Turbo-charging hidden database samplers with overflowing queries and skew reduction
Recently, there has been growing interest in random sampling from online hidden databases. These databases reside behind form-like web interfaces which allow users to execute sear...
Arjun Dasgupta, Nan Zhang 0004, Gautam Das
JMLR
2006
99views more  JMLR 2006»
13 years 7 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...