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» Approximation algorithms for projective clustering
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SODA
2010
ACM
164views Algorithms» more  SODA 2010»
15 years 8 months ago
Differentially Private Approximation Algorithms
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...
ICALP
2010
Springer
15 years 3 months ago
Clustering with Diversity
Abstract. We consider the clustering with diversity problem: given a set of colored points in a metric space, partition them into clusters such that each cluster has at least point...
Jian Li, Ke Yi, Qin Zhang
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
15 years 11 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li
FOCS
2005
IEEE
15 years 4 months ago
How to Pay, Come What May: Approximation Algorithms for Demand-Robust Covering Problems
Robust optimization has traditionally focused on uncertainty in data and costs in optimization problems to formulate models whose solutions will be optimal in the worstcase among ...
Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Sing...
ICDCS
2006
IEEE
15 years 5 months ago
Fault-Tolerant Clustering in Ad Hoc and Sensor Networks
In this paper, we study distributed approximation algorithms for fault-tolerant clustering in wireless ad hoc and sensor networks. A k-fold dominating set of a graph G = (V, E) is...
Fabian Kuhn, Thomas Moscibroda, Roger Wattenhofer