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» A Nonparametric Approach to Noisy and Costly Optimization
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GECCO
2004
Springer
118views Optimization» more  GECCO 2004»
13 years 10 months ago
Adaptive Sampling for Noisy Problems
Abstract. The usual approach to deal with noise present in many realworld optimization problems is to take an arbitrary number of samples of the objective function and use the samp...
Erick Cantú-Paz
MICCAI
2010
Springer
13 years 3 months ago
Reconstructing Geometrically Consistent Tree Structures from Noisy Images
Abstract. We present a novel approach to fully automated reconstruction of tree structures in noisy 2D images. Unlike in earlier approaches, we explicitly handle crossovers and bif...
Engin Türetken, Christian Blum, Germán...
CVPR
2007
IEEE
14 years 3 months ago
Simultaneous Depth Reconstruction and Restoration of Noisy Stereo Images Using Non-local Pixel Distribution
In this paper, we propose a new algorithm that solves both the stereo matching and the image denoising problem simultaneously for a pair of noisy stereo images. Most stereo algorit...
Yong Seok Heo (Seoul National University), Kyoung ...
ICML
2009
IEEE
14 years 6 months ago
SimpleNPKL: simple non-parametric kernel learning
Previous studies of Non-Parametric Kernel (NPK) learning usually reduce to solving some Semi-Definite Programming (SDP) problem by a standard SDP solver. However, time complexity ...
Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi
PR
2008
131views more  PR 2008»
13 years 5 months ago
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
Salvador García, José Ramón C...