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» Model Selection for Small Sample Regression
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ESEM
2007
ACM
13 years 11 months ago
The Effects of Over and Under Sampling on Fault-prone Module Detection
The goal of this paper is to improve the prediction performance of fault-prone module prediction models (fault-proneness models) by employing over/under sampling methods, which ar...
Yasutaka Kamei, Akito Monden, Shinsuke Matsumoto, ...
ICML
2008
IEEE
14 years 8 months ago
Bolasso: model consistent Lasso estimation through the bootstrap
We consider the least-square linear regression problem with regularization by the 1-norm, a problem usually referred to as the Lasso. In this paper, we present a detailed asymptot...
Francis R. Bach
TIP
2010
155views more  TIP 2010»
13 years 5 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
CEC
2009
IEEE
14 years 2 months ago
Coevolution of simulator proxies and sampling strategies for petroleum reservoir modeling
— Reservoir modeling is an on-going activity during the production life of a reservoir. One challenge to constructing accurate reservoir models is the time required to carry out ...
Tina Yu, Dave Wilkinson
DATE
2010
IEEE
153views Hardware» more  DATE 2010»
14 years 17 days ago
HORUS - high-dimensional Model Order Reduction via low moment-matching upgraded sampling
— This paper describes a Model Order Reduction algorithm for multi-dimensional parameterized systems, based on a sampling procedure which incorporates a low order moment matching...
Jorge Fernandez Villena, Luis Miguel Silveira