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» Learning from Multiple Annotators with Gaussian Processes
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ECCV
2010
Springer
13 years 4 months ago
Coupled Gaussian Process Regression for Pose-Invariant Facial Expression Recognition
We present a novel framework for the recognition of facial expressions at arbitrary poses that is based on 2D geometric features. We address the problem by first mapping the 2D loc...
Ognjen Rudovic, Ioannis Patras, Maja Pantic
ICASSP
2010
IEEE
13 years 4 months ago
Disambiguation in multidimensional tracking of multiple acoustic sources using a Gaussian likelihood criterion
The TDOA-based acoustic source localization approaches suffer from a pairing problem in the case of multiple dimensions and multiple sources. To resolve this problem, usually thre...
Pengxiao Teng, Anthony Lombard, Walter Kellermann
BMCBI
2011
12 years 10 months ago
Improving pan-genome annotation using whole genome multiple alignment
Background: Rapid annotation and comparisons of genomes from multiple isolates (pan-genomes) is becoming commonplace due to advances in sequencing technology. Genome annotations c...
Samuel V. Angiuoli, Julie C. Dunning Hotopp, Steve...
EMNLP
2009
13 years 4 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
Gregory Druck, Burr Settles, Andrew McCallum
JMLR
2010
129views more  JMLR 2010»
13 years 1 months ago
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...