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SIGIR
2006
ACM
13 years 11 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
NIPS
2001
13 years 6 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi
ICPP
2009
IEEE
13 years 12 months ago
Run to Potential: Sweep Coverage in Wireless Sensor Networks
—Wireless sensor networks have become a promising technology in monitoring physical world. In many applications with wireless sensor networks, it is essential to understand how w...
Min Xi, Kui Wu, Yong Qi, Jizhong Zhao, Yunhao Liu,...