Karl Bringmann
Karl Bringmann
Professor in Computer Science, Saarland University
Verified email at - Homepage
Cited by
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Why walking the dog takes time: Frechet distance has no strongly subquadratic algorithms unless SETH fails
K Bringmann
2014 IEEE 55th Annual Symposium on Foundations of Computer Science, 661-670, 2014
Quadratic conditional lower bounds for string problems and dynamic time warping
K Bringmann, M Künnemann
2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 79-97, 2015
Approximating the volume of unions and intersections of high-dimensional geometric objects
K Bringmann, T Friedrich
Computational Geometry 43 (6-7), 601-610, 2010
Approximating the least hypervolume contributor: NP-hard in general, but fast in practice
K Bringmann, T Friedrich
Theoretical Computer Science 425, 104-116, 2012
Geometric inhomogeneous random graphs
K Bringmann, R Keusch, J Lengler
Theoretical Computer Science 760, 35-54, 2019
A near-linear pseudopolynomial time algorithm for subset sum
K Bringmann
Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017
An efficient algorithm for computing hypervolume contributions
K Bringmann, T Friedrich
Evolutionary Computation 18 (3), 383-402, 2010
Approximation-guided evolutionary multi-objective optimization
K Bringmann, T Friedrich, F Neumann, M Wagner
IJCAI Proceedings-International Joint Conference on Artificial Intelligence …, 2011
Approximability of the discrete Fréchet distance
K Bringmann, W Mulzer
Journal of Computational Geometry 7 (2), 46–76-46–76, 2016
SETH-based lower bounds for subset sum and bicriteria path
A Abboud, K Bringmann, D Hermelin, D Shabtay
ACM Transactions on Algorithms (TALG) 18 (1), 1-22, 2022
Approximation quality of the hypervolume indicator
K Bringmann, T Friedrich
Artificial Intelligence 195, 265-290, 2013
Truly subcubic algorithms for language edit distance and RNA folding via fast bounded-difference min-plus product
K Bringmann, F Grandoni, B Saha, VV Williams
SIAM Journal on Computing 48 (2), 481-512, 2019
Efficient sampling methods for discrete distributions
K Bringmann, K Panagiotou
Algorithmica 79, 484-508, 2017
Two-dimensional subset selection for hypervolume and epsilon-indicator
K Bringmann, T Friedrich, P Klitzke
Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014
Multivariate fine-grained complexity of longest common subsequence
K Bringman, M Künnemann
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018
Tree edit distance cannot be computed in strongly subcubic time (unless APSP can)
K Bringmann, P Gawrychowski, S Mozes, O Weimann
ACM Transactions on Algorithms (TALG) 16 (4), 1-22, 2020
A dichotomy for regular expression membership testing
K Bringmann, A Grřnlund, KG Larsen
2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017
Don't be greedy when calculating hypervolume contributions
K Bringmann, T Friedrich
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic …, 2009
Sampling geometric inhomogeneous random graphs in linear time
K Bringmann, R Keusch, J Lengler
arXiv preprint arXiv:1511.00576, 2015
A PTAS for p-Low Rank Approximation
F Ban, V Bhattiprolu, K Bringmann, P Kolev, E Lee, DP Woodruff
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019
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