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GFKL
2007
Springer
163views Data Mining» more  GFKL 2007»
15 years 7 months ago
Fast Support Vector Machine Classification of Very Large Datasets
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...
Janis Fehr, Karina Zapien Arreola, Hans Burkhardt
109
Voted
ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
15 years 10 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
156
Voted
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 4 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
123
Voted
ICALT
2003
IEEE
15 years 9 months ago
Evaluating the Role of a Shared Document-Based Annotation Tool in Learner-Centered Collaborative Learning
This study presents a shared document-based annotation tool, EDUCOSM. Usefulness of the system is empirically evaluated in a real-life collaborative learning context. Relationship...
Petri Nokelainen, Jaakko Kurhila, Miikka Miettinen...
162
Voted
DAGSTUHL
2009
15 years 4 months ago
Statistical Mechanics of On-line Learning
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...
Michael Biehl, Nestor Caticha, Peter Riegler