Searching for "Approximation Algorithms for Clustering Problems." – sorted by Relevance.
-
Approximation Algorithms for Clustering Problems
- APPROXIMATION ALGORITHMS FOR CLUSTERING PROBLEMS A Dissertation Presented to the Faculty
- Cited by 12 (4 self) – Add To MetaCart
-
Subquadratic Approximation Algorithms For Clustering Problems in High Dimensional Spaces
- Subquadratic Approximation Algorithms For Clustering Problems in High Dimensional Spaces Allan
- Cited by 16 (1 self) – Add To MetaCart
-
K.: Private approximation of clustering and vertex
- of vertices in the graph). For the clustering problems we prove that even approximation algorithms with a poor
- Cited by 1 (1 self) – Add To MetaCart
-
Linear time algorithms for clustering problems in any dimensions
- -means clustering problems, resulting in O(2 (k/ε)O(1) dn) time (1 + ε)-approximation algorithms for these problems
- Cited by 6 (0 self) – Add To MetaCart
-
An Efficient Approximation Scheme for Data Mining Tasks
- detection algorithms to provide accurate approximate solutions to these problems. 3.1 Clustering We run
- Cited by 9 (0 self) – Add To MetaCart
-
An asymptotic O(ln ρ/ ln ln ρ)-approximation algorithm for the scheduling problem
- , if duplication appears to be a useful technic to get approximation algorithms for the clustering problem, very
- Add To MetaCart
-
Facility location in sublinear time
- gigabytes. For example, when we consider approximation algorithms for clustering problems in metric spaces
- Cited by 5 (1 self) – Add To MetaCart
-
unknown title
- . Rabani. Subquadratic approximation algorithms for clustering problems in high dimensional spaces. In Proc
- Add To MetaCart

