3874 search results - page 479 / 775 » Approximation Algorithms for k-hurdle Problems |
187
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FOCS
2010
IEEE
15 years 3 months ago
2010
IEEE
We consider k-median clustering in finite metric spaces and k-means clustering in Euclidean spaces, in the setting where k is part of the input (not a constant). For the k-means pr...
196
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SODA
2010
ACM
16 years 2 months ago
2010
ACM
Bidimensionality theory appears to be a powerful framework in the development of meta-algorithmic techniques. It was introduced by Demaine et al. [J. ACM 2005 ] as a tool to obtai...
138
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STOC
2007
ACM
16 years 5 months ago
2007
ACM
We demonstrate an average-case problem that is as hard as finding (n)-approximate shortest vectors in certain n-dimensional lattices in the worst case, where (n) = O( log n). The...
128
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ICML
2005
IEEE
16 years 6 months ago
2005
IEEE
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
125
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STOC
2004
ACM
16 years 5 months ago
2004
ACM
A flow is said to be confluent if at any node all the flow leaves along a single edge. Given a directed graph G with k sinks and non-negative demands on all the nodes of G, we con...