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» Robust Regression with Twinned Gaussian Processes
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ICIP
2006
IEEE
14 years 9 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
BMVC
2010
13 years 5 months ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata
RSS
2007
159views Robotics» more  RSS 2007»
13 years 9 months ago
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
Christian Plagemann, Kristian Kersting, Patrick Pf...
ICASSP
2011
IEEE
12 years 11 months ago
Gaussian Mixture Modeling of vowel durations for automated assessment of non-native speech
This paper investigates using Gaussian Mixture Model (GMM) based vowel duration features for automated assessment of non-native speech. Two different types of models were compared...
Xie Sun, Keelan Evanini
NIPS
2007
13 years 9 months ago
Selecting Observations against Adversarial Objectives
In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well...
Andreas Krause, H. Brendan McMahan, Carlos Guestri...