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GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 6 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
15 years 1 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
NIPS
2008
15 years 1 months ago
Bayesian Kernel Shaping for Learning Control
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...
ICRA
2008
IEEE
149views Robotics» more  ICRA 2008»
15 years 6 months ago
Monocular range sensing: A non-parametric learning approach
Abstract— Mobile robots rely on the ability to sense the geometry of their local environment in order to avoid obstacles or to explore the surroundings. For this task, dedicated ...
Christian Plagemann, Felix Endres, Juergen Michael...
ICCV
2005
IEEE
15 years 5 months ago
Learning Models for Predicting Recognition Performance
This paper addresses one of the fundamental problems encountered in performance prediction for object recognition. In particular we address the problems related to estimation of s...
Rong Wang, Bir Bhanu