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WSDM
2010
ACM
254views Data Mining» more  WSDM 2010»
16 years 3 months ago
Learning Influence Probabilities In Social Networks
Recently, there has been tremendous interest in the phenomenon of influence propagation in social networks. The studies in this area assume they have as input to their problems a ...
Amit Goyal 0002, Francesco Bonchi, Laks V. S. Laks...
WAIM
2009
Springer
15 years 10 months ago
Kernel-Based Transductive Learning with Nearest Neighbors
In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...
Liangcai Shu, Jinhui Wu, Lei Yu, Weiyi Meng
IJOE
2007
107views more  IJOE 2007»
15 years 6 months ago
Learning Digital Test and Diagnostics via Internet
: An environment targeted to e-learning is presented for teaching design and test of electronic systems. The environment consists of a set of Java applets, and of web based access ...
Raimund Ubar, Artur Jutman, Margus Kruus, Elmet Or...
NIPS
2003
15 years 7 months ago
Learning the k in k-means
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...
Greg Hamerly, Charles Elkan
NN
2007
Springer
106views Neural Networks» more  NN 2007»
15 years 5 months ago
Machine learning approach to color constancy
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Vivek Agarwal, Andrei V. Gribok, Mongi A. Abidi