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» Set cover algorithms for very large datasets
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NIPS
2004
15 years 7 months ago
Hierarchical Eigensolver for Transition Matrices in Spectral Methods
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Chakra Chennubhotla, Allan D. Jepson
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
13 years 8 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
IPPS
1997
IEEE
15 years 9 months ago
Designing Efficient Distributed Algorithms Using Sampling Techniques
In this paper we show the power of sampling techniques in designing efficient distributed algorithms. In particular, we show that using sampling techniques, on some networks, sele...
Sanguthevar Rajasekaran, David S. L. Wei
PAM
2010
Springer
16 years 27 days ago
Extracting Intra-domain Topology from mrinfo Probing
Active and passive measurements for topology discovery have known an impressive growth during the last decade. If a lot of work has been done regarding inter-domain topology discov...
Jean-Jacques Pansiot, Pascal Mérindol, Beno...
CVPR
2008
IEEE
16 years 8 months ago
A Parallel Decomposition Solver for SVM: Distributed dual ascend using Fenchel Duality
We introduce a distributed algorithm for solving large scale Support Vector Machines (SVM) problems. The algorithm divides the training set into a number of processing nodes each ...
Tamir Hazan, Amit Man, Amnon Shashua