Prof. Dr. Heiko Röglin

Summer 2016: Randomized Algorithms & Probabilistic Analysis

• A. Gupta, G. Guruganesh, M.S.: Approximation algorithms for aversion k-clustering via local k-median. ICALP 2016: to appear. Talk
• J. Blömer, C. Lammersen, M.S., C. Sohler: Theoretical Analysis of the k-Means Algorithm - A Survey, CORR, 2016, arXiv:1602.08254
• E. Lee, M.S., J. Wright: Improved and Simplified Inapproximability for k-means, CORR, 2015, arXiv:1509.00916. Talk
• J.-P. W. Kappmeier, D. R. Schmidt, M.S.: Solving k-means on High-Dimensional Big Data. SEA 2015: 259-270, arXiv:1502.04265
• H. Fichtenberger, M. Gillé, M.S., C. Schwiegelshohn, C. Sohler: BICO: BIRCH Meets Coresets for k-Means Clustering. ESA 2013
  en/staff/mschmidt.txt · Zuletzt geändert: 2016/06/30 22:36 von schmidt