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TMC
2010
167views more  TMC 2010»
15 years 1 months ago
Optimal Speed Control of Mobile Node for Data Collection in Sensor Networks
A data mule represents a mobile device that collects data in a sensor field by physically visiting the nodes in a sensor network. The data mule collects data when it is in the prox...
Ryo Sugihara, Rajesh K. Gupta
TKDE
2012
245views Formal Methods» more  TKDE 2012»
13 years 9 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
ACL
2008
15 years 8 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
CORR
2008
Springer
151views Education» more  CORR 2008»
15 years 6 months ago
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling...
Joel A. Tropp, Deanna Needell
CCECE
2006
IEEE
16 years 23 days ago
New Constraints on Generation of Uniform Random Samples from Evolutionary Trees
In this paper, we introduce new algorithms for selecting taxon samples from large evolutionary trees, maintaining uniformity and randomness, under certain new constraints on the t...
Anupam Bhattacharjee, Zalia Shams, Kazi Zakia Sult...