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87
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ESANN
2007
15 years 2 months ago
Learning topology of a labeled data set with the supervised generative gaussian graph
Abstract. Discovering the topology of a set of labeled data in a Euclidian space can help to design better decision systems. In this work, we propose a supervised generative model ...
Pierre Gaillard, Michaël Aupetit, Géra...
114
Voted
ICNC
2005
Springer
15 years 6 months ago
An Incremental Learning Method Based on SVM for Online Sketchy Shape Recognition
This paper presents briefly an incremental learning method based on SVM for online sketchy shape recognition. It can collect all classified results corrected by user and select som...
Zhengxing Sun, Lisha Zhang, Enyi Tang
IJCAI
2003
15 years 1 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
87
Voted
ECML
2006
Springer
15 years 4 months ago
Graph Based Semi-supervised Learning with Sharper Edges
In many graph-based semi-supervised learning algorithms, edge weights are assumed to be fixed and determined by the data points' (often symmetric) relationships in input space...
Hyunjung Shin, N. Jeremy Hill, Gunnar Rätsch
SAC
2006
ACM
15 years 6 months ago
Discretization from data streams: applications to histograms and data mining
Abstract. In this paper we propose a new method to perform incremental discretization. The basic idea is to perform the task in two layers. The first layer receives the sequence o...
João Gama, Carlos Pinto