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» Heteroscedastic Gaussian process regression
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98
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TIP
2008
128views more  TIP 2008»
14 years 11 months ago
The Pairing of a Wavelet Basis With a Mildly Redundant Analysis via Subband Regression
A distinction is usually made between wavelet bases and wavelet frames. The former are associated with a one-to-one representation of signals, which is somewhat constrained but mos...
Michael Unser, Dimitri Van De Ville
116
Voted
ICIP
2006
IEEE
16 years 1 months ago
Robust Kernel Regression for Restoration and Reconstruction of Images from Sparse Noisy Data
We introduce a class of robust non-parametric estimation methods which are ideally suited for the reconstruction of signals and images from noise-corrupted or sparsely collected s...
Hiroyuki Takeda, Sina Farsiu, Peyman Milanfar
IJCNN
2008
IEEE
15 years 6 months ago
A neural network approach to ordinal regression
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
Jianlin Cheng, Zheng Wang, Gianluca Pollastri
111
Voted
CVPR
2008
IEEE
16 years 1 months ago
Sparse probabilistic regression for activity-independent human pose inference
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...
Raquel Urtasun, Trevor Darrell
ICRA
2009
IEEE
166views Robotics» more  ICRA 2009»
15 years 6 months ago
Anatomically correct testbed hand control: Muscle and joint control strategies
— Human hands are capable of many dexterous grasping and manipulation tasks. To understand human levels of dexterity and to achieve it with robotic hands, we constructed an anato...
Ashish Deshpande, Jonathan Ko, Dieter Fox, Yoky Ma...