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ICANN
2011
Springer
12 years 10 months ago
Bias of Importance Measures for Multi-valued Attributes and Solutions
Attribute importance measures for supervised learning are important for improving both learning accuracy and interpretability. However, it is well-known there could be bias when th...
Houtao Deng, George C. Runger, Eugene Tuv
ETT
2002
77views Education» more  ETT 2002»
13 years 7 months ago
On the importance function in splitting simulation
The splitting method is a simulation technique for the estimation of very small probabilities. In this technique, the sample paths are split into multiple copies, at various stages...
Marnix J. J. Garvels, Jan-Kees C. W. van Ommeren, ...
HVEI
2010
13 years 5 months ago
Quantifying the relationship between visual salience and visual importance
This paper presents the results of two psychophysical experiments and an associated computational analysis designed to quantify the relationship between visual salience and visual...
Junle Wang, Damon M. Chandler, Patrick Le Callet
UAI
2000
13 years 8 months ago
Adaptive Importance Sampling for Estimation in Structured Domains
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Luis E. Ortiz, Leslie Pack Kaelbling
CGF
2004
158views more  CGF 2004»
13 years 7 months ago
Combined Correlated and Importance Sampling in Direct Light Source Computation and Environment Mapping
This paper presents a general variance reduction method that is a quasi-optimal combination of correlated and importance sampling. The weights of the combination are selected auto...
László Szécsi, Mateu Sbert, L...