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» Margin Based Active Learning
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FMSD
2008
110views more  FMSD 2008»
13 years 10 months ago
Automatic symbolic compositional verification by learning assumptions
Abstract Compositional reasoning aims to improve scalability of verification tools by reducing the original verification task into subproblems. The simplification is typically base...
Wonhong Nam, P. Madhusudan, Rajeev Alur
ECSCW
2003
13 years 11 months ago
Learning and Living in the 'New office'
‘Knowledge sharing’ and ‘learning’ are terms often connected with the ‘New office’, the “modern” open office space. Work in these settings becomes more and more dis...
Eva Bjerrum, Susanne Bødker
PR
2006
89views more  PR 2006»
13 years 10 months ago
Gaussian fields for semi-supervised regression and correspondence learning
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
Jakob J. Verbeek, Nikos A. Vlassis
ICASSP
2011
IEEE
13 years 1 months ago
Versatile and portable DSP platform for learning embedded signal processing
This paper presents a versatile and portable digital signal processing (DSP) platform that is highly suitable for learning embedded signal processing anywhere and anytime. This DS...
Woon-Seng Gan, Abhishek Seth, Sen M. Kuo
ICWE
2005
Springer
14 years 3 months ago
An Application Framework for Collaborative Learning
We present the design of a new web application framework for collaborative learning. The framework guides users (i.e. teachers) in implementing online activities based on well-know...
Aiman Turani, Rafael A. Calvo, Peter Goodyear