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JMLR
2010
130views more  JMLR 2010»
13 years 2 months ago
A Regularization Approach to Nonlinear Variable Selection
In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based o...
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Ales...
ICASSP
2010
IEEE
13 years 8 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
CIAC
2000
Springer
105views Algorithms» more  CIAC 2000»
14 years 7 days ago
Algorithms for a Simple Point Placement Problem
We consideralgorithms for a simple one-dimensionalpoint placement problem: given N points on a line, and noisy measurements of the distances between many pairs of them, estimate th...
Joshua Redstone, Walter L. Ruzzo
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
MVA
2007
132views Computer Vision» more  MVA 2007»
13 years 9 months ago
A Robust Coarse-to-Fine Method for Pupil Localization in Non-ideal Eye Images
Pupil localization is a very important preprocessing step in many machine vision applications. Accurate and robust pupil localization especially in non-ideal eye images (such as i...
Xiaoyan Yuan, Pengfei Shi