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CVPR
2009
IEEE
1372views Computer Vision» more  CVPR 2009»
15 years 3 months ago
Blind motion deblurring from a single image using sparse approximation
Restoring a clear image from a single motion-blurred image due to camera shake has long been a challenging problem in digital imaging. Existing blind deblurring techniques eithe...
Jian-Feng Cai (National University of Singapore), ...
NIPS
2004
13 years 10 months ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu
DCG
2008
93views more  DCG 2008»
13 years 8 months ago
Robust Shape Fitting via Peeling and Grating Coresets
Let P be a set of n points in Rd . A subset S of P is called a (k, )-kernel if for every direction, the direction width of S -approximates that of P, when k "outliers" c...
Pankaj K. Agarwal, Sariel Har-Peled, Hai Yu
AAAI
2012
11 years 11 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
ICANN
2005
Springer
14 years 2 months ago
Informational Energy Kernel for LVQ
We describe a kernel method which uses the maximization of Onicescu’s informational energy as a criteria for computing the relevances of input features. This adaptive relevance d...
Angel Cataron, Razvan Andonie