In a recent breakthrough, Chen, Kyng, Liu, Peng, Probst Gutenberg, and Sachdeva (arXiv:2203.00671) designed the first almost-linear-time algorithm for minimum-cost flow. Their approach uses an Interior Point Method (IPM) to achieve complexity $m^{1+o(1)}\log U \log C$. However, the $m^{1+o(1)}$ factor hides intricate r...
Emil Schätzle, Simon Meierhans, Rasmus Kyng et al.· 1 citation
The original online leverage-score sampling algorithm is indeed robust to adaptive adversaries and is given the first online sparsification algorithm for adaptive streams that yields a sparsifier of near-optimal size $O(d \varepsilon^{-2}\log^2 d)$ whose working memory is proportional to the size of the sparsifier.
Gramoz Goranci, Rasmus Kyng, Maximilian Probst Gutenberg et al.· arXiv.org· 1 citation
This work presents the first polylog-depth, nearly-linear-work parallel algorithm that achieves a (1 + ε )- bicriteria approximation guarantee for undirected minimum-cost flow on expanders and suggests a promising route toward e O ( m/ε ) work and e O (1 /ε ) depth algorithms for approximate undirected minimum-cost flo...
Rasmus Kyng, Aurelio L. Sulser· International Colloquium on...· 0 citations
A randomized data structure for undirected weighted graphs that are partially dynamic, i.e., that undergo either only edge insertions or only edge deletions is given, which follows from a simple stability principle for partially dynamic graphs.
Gramoz Goranci, Rasmus Kyng, Maximilian Probst Gutenberg et al.· 0 citations
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