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» Boosting Methods for Regression
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ICASSP
2007
IEEE
14 years 4 months ago
Kernel Resolution Synthesis for Superresolution
Abstract— This work considers a combination classificationregression based framework with the proposal of using learned kernels in modified support vector regression to provide...
Karl S. Ni, Truong Nguyen
NIPS
2007
13 years 11 months ago
Hierarchical Penalization
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...
CEC
2011
IEEE
12 years 10 months ago
Trainer selection strategies for coevolving rank predictors
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
Daniel L. Ly, Hod Lipson

Publication
336views
12 years 2 months ago
Feature Mining for Localised Crowd Counting
This paper presents a multi-output regression model for crowd counting in public scenes. Existing counting by regression methods either learn a single model for global counting, or...
Ke Chen, Chen Change Loy, Shaogang Gong, Tao Xiang...
ICPR
2010
IEEE
13 years 8 months ago
A Re-evaluation of Pedestrian Detection on Riemannian Manifolds
Abstract--Boosting covariance data on Riemannian manifolds has proven to be a convenient strategy in a pedestrian detection context. In this paper we show that the detection perfor...
Diego Tosato, Michela Farenzena, Marco Cristani, V...