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» A Framework for Multiple-Instance Learning
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ICDAR
2005
IEEE
15 years 9 months ago
Learning Diagram Parts with Hidden Random Fields
Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
Martin Szummer
ICTAI
2005
IEEE
15 years 9 months ago
Latent Process Model for Manifold Learning
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
CSCWD
2005
Springer
15 years 9 months ago
Towards an engineering approach for groupware development: learning from the AulaNet LMS development
This paper presents the AulaNet learning management system, its architecture and the collaboration model that guided its development and that was refined during this process. A ca...
Marco Aurélio Gerosa, Mariano Gomes Pimente...
KES
2005
Springer
15 years 9 months ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh
121
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COLT
2004
Springer
15 years 9 months ago
Regularization and Semi-supervised Learning on Large Graphs
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Mikhail Belkin, Irina Matveeva, Partha Niyogi