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» Approximation Algorithms for Data Placement Problems
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STOC
2003
ACM
141views Algorithms» more  STOC 2003»
14 years 8 months ago
Better streaming algorithms for clustering problems
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
Moses Charikar, Liadan O'Callaghan, Rina Panigrahy
SODA
2010
ACM
171views Algorithms» more  SODA 2010»
14 years 5 months ago
Coresets and Sketches for High Dimensional Subspace Approximation Problems
We consider the problem of approximating a set P of n points in Rd by a j-dimensional subspace under the p measure, in which we wish to minimize the sum of p distances from each p...
Dan Feldman, Morteza Monemizadeh, Christian Sohler...
TAMC
2007
Springer
14 years 1 months ago
Approximability and Parameterized Complexity of Consecutive Ones Submatrix Problems
Abstract. We develop a refinement of a forbidden submatrix characterization of 0/1-matrices fulfilling the Consecutive Ones Property (C1P). This novel characterization finds app...
Michael Dom, Jiong Guo, Rolf Niedermeier
PODS
2008
ACM
159views Database» more  PODS 2008»
14 years 7 months ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor
COCOON
2007
Springer
14 years 1 months ago
Priority Algorithms for the Subset-Sum Problem
Greedy algorithms are simple, but their relative power is not well understood. The priority framework [5] captures a key notion of “greediness” in the sense that it processes (...
Yuli Ye, Allan Borodin