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» Using feature models to automate model transformations
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NIPS
2003
15 years 8 months ago
Warped Gaussian Processes
We generalise the Gaussian process (GP) framework for regression by learning a nonlinear transformation of the GP outputs. This allows for non-Gaussian processes and non-Gaussian ...
Edward Snelson, Carl Edward Rasmussen, Zoubin Ghah...
FGR
2011
IEEE
268views Biometrics» more  FGR 2011»
14 years 10 months ago
Emotion recognition using PHOG and LPQ features
— We propose a method for automatic emotion recognition as part of the FERA 2011 competition [1] . The system extracts pyramid of histogram of gradients (PHOG) and local phase qu...
Abhinav Dhall, Akshay Asthana, Roland Goecke, Tom ...
IPPS
1999
IEEE
15 years 11 months ago
A Structured Approach to Parallel Programming: Methodology and Models
Parallel programming continues to be difficult, despite substantial and ongoing research aimed at making it tractable. Especially dismaying is the gulf between theory and the pract...
Berna L. Massingill
AUSAI
2007
Springer
15 years 11 months ago
Building Classification Models from Microarray Data with Tree-Based Classification Algorithms
Building classification models plays an important role in DNA mircroarray data analyses. An essential feature of DNA microarray data sets is that the number of input variables (gen...
Peter J. Tan, David L. Dowe, Trevor I. Dix
NIPS
2000
15 years 8 months ago
Recognizing Hand-written Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a non-linear generative model of handwritten images of digits. The q...
Guy Mayraz, Geoffrey E. Hinton