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20192023
most citedk-means++: few more steps yield constant approximation

5 citations · 8 across the 9 of their papers we have counts for

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cs.DS2023

Work-Efficient Parallel Derandomization II: Optimal Concentrations via Bootstrapping

Mohsen Ghaffari, Christoph Grunau

We present an efficient parallel derandomization method for randomized algorithms that rely on concentrations such as the Chernoff bound. This settles a classic problem in parallel…

cs.DS2023

Work-Efficient Parallel Derandomization I: Chernoff-like Concentrations via Pairwise Independence

Mohsen Ghaffari, Christoph Grunau, Václav Rozhoň

We present a novel technique for work-efficient parallel derandomization, for algorithms that rely on the concentration of measure bounds such as Chernoff, Hoeffding, and Bernstein…

cs.DS2023

Fully Dynamic Consistent -Center Clustering

Jakub Łącki, Bernhard Haeupler, Christoph Grunau +2

We study the consistent k-center clustering problem. In this problem, the goal is to maintain a constant factor approximate -center solution during a sequence of point inser…

cs.DS20231 cited

Noisy k-means++ Revisited

Christoph Grunau, Ahmet Alper Özüdoğru, Václav Rozhoň

The -means++ algorithm by Arthur and Vassilvitskii [SODA 2007] is a classical and time-tested algorithm for the -means problem. While being very practical, the algorithm also…

cs.DS2023

Nearly Work-Efficient Parallel DFS in Undirected Graphs

Mohsen Ghaffari, Christoph Grunau, Jiahao Qu

We present the first parallel depth-first search algorithm for undirected graphs that has near-linear work and sublinear depth. Concretely, in any -node -edge undirected grap…

cs.DS2023

Faster Deterministic Distributed MIS and Approximate Matching

Mohsen Ghaffari, Christoph Grunau

We present an round deterministic distributed algorithm for the maximal independent set problem. By known reductions, thi…