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JMLR
2010
147views more  JMLR 2010»
14 years 5 months ago
Gaussian Processes for Machine Learning (GPML) Toolbox
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
Carl Edward Rasmussen, Hannes Nickisch
80
Voted
ICALT
2010
IEEE
14 years 8 months ago
Modelling Affect in Learning Environments - Motivation and Methods
Emotions have a functional relevance to learning and achievement. Not surprisingly then, affective diagnoses are an important aspect of expert human mentoring. Computerbased learni...
Shazia Afzal, Peter Robinson
95
Voted
PROPERTYTESTING
2010
14 years 8 months ago
Testing by Implicit Learning: A Brief Survey
We give a high-level survey of the "testing by implicit learning" paradigm, and explain some of the property testing results for various Boolean function classes that ha...
Rocco A. Servedio
79
Voted
LFCS
1992
Springer
15 years 2 months ago
Machine Learning of Higher Order Programs
A generator program for a computable function (by definition) generates an infinite sequence of programs all but finitely many of which compute that function. Machine learning of ...
Ganesh Baliga, John Case, Sanjay Jain, Mandayam Su...
ICPR
2008
IEEE
15 years 11 months ago
Collaborative learning by boosting in distributed environments
In this paper we propose a new distributed learning method called distributed network boosting (DNB) algorithm for distributed applications. The learned hypotheses are exchanged b...
Shijun Wang, Changshui Zhang