On approximating the smallest enclosing bregman balls

Proceedings of the Annual Symposium on Computational Geometry

Volumn 2006, Issue , 2006, Pages 485-486

  Nielsen, Frank ^a   Nock, Richard ^b  

^a SONY COMPUTER SCIENCE LABORATORIES INC   (Japan)

^b UNIVERSITÉ DES ANTILLES ET DE LA GUYANE   (France)

Author keywords

Bregman divergence; Core set; Minimum enclosing ball

Indexed keywords

ALGORITHMIC LANGUAGES; APPROXIMATION THEORY; COMPUTATIONAL METHODS; CONVERGENCE OF NUMERICAL METHODS; PROBLEM SOLVING; SET THEORY;

BREGMAN DIVERGENCE; CLARKSON'S ALGORITHMS; CORE SETS; MINIMUM ENCLOSING BALLS;

COMPUTATIONAL GEOMETRY;

EID: 33748050777     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1137856.1137931     Document Type: Conference Paper

References (4)

1. F. Nielsen and R. Nock. Approximating smallest enclosing balls. In ICCSA CGA, pp. 147-157. LNCS #3045, Springer-Verlag, pp. 147-157, 2004.
2. A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh. Clustering with Bregman divergences. In Journal of Machine Learning (JMLR), 6:1705-1749, 2005.
3. M. Bǎdoiu and K. L. Clarkson. Smaller core-sets for balls. In ACM-SIAM Sympos. Discret Algorithms, pp. 801-802, 2003. http://cm.bell-labs.com/ who/clarkson/
4. R. Nock and F. Nielsen. Fitting the smallest enclosing Bregman ball. In European Conference on Machine Learning (ECML), LNCS #3720, pp. 649-656, 2005.