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ICML
2005
IEEE
16 years 4 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
ICML
2007
IEEE
16 years 4 months ago
Efficiently computing minimax expected-size confidence regions
Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
ISESE
2006
IEEE
15 years 9 months ago
Using observational pilot studies to test and improve lab packages
Controlled experiments are a key approach to evaluate and evolve our understanding of software engineering technologies. However, defining and running a controlled experiment is a...
Manoel G. Mendonça, Daniela Cruzes, Josemei...
ECTEL
2007
Springer
15 years 9 months ago
Resolving Variations in Learning Spaces for Experiential Learning
Today, systems should react based on explicit demands from the learner or even proactively react based on changes in the working environment. The success of this type of systems de...
Eric Ras
CGF
2005
252views more  CGF 2005»
15 years 3 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...