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» Classification of unlabeled point sets using ANSIG
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KDD
2008
ACM
259views Data Mining» more  KDD 2008»
15 years 10 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
DAGM
2004
Springer
15 years 2 months ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf
98
Voted
IJCAI
2003
14 years 11 months ago
Integrating Background Knowledge Into Text Classification
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
Sarah Zelikovitz, Haym Hirsh
ICML
2007
IEEE
15 years 10 months ago
The rendezvous algorithm: multiclass semi-supervised learning with Markov random walks
We consider the problem of multiclass classification where both labeled and unlabeled data points are given. We introduce and demonstrate a new approach for estimating a distribut...
Arik Azran
ICIP
2009
IEEE
14 years 7 months ago
Shapes as empirical distributions
We address the problem of shape based classification. We interpret the shape of an object as a probability distribution governing the location of the points of the object. An imag...
Bernardo Rodrigues Pires, José M. F. Moura