Anurag Ajay, Seungwook Han, et al.
NeurIPS 2023
We show that the sparsest cut in graphs with n vertices and m edges can be approximated within O(log 2 n) factor in (m + n 3/2) time using polylogarithmic single commodity max-flow computations. Previous algorithms are based on multicommodity flows that take time (m + n 2). Our algorithm iteratively employs max-flow computations to embed an expander flow, thus providing a certificate of expansion. Our technique can also be extended to yield an O(log 2 n)-(pseudo-) approximation algorithm for the edge-separator problem with a similar running time. © 2009 ACM.
Anurag Ajay, Seungwook Han, et al.
NeurIPS 2023
Zhikun Yuen, Paula Branco, et al.
DSAA 2023
Danila Seliayeu, Quinn Pham, et al.
CASCON 2024
Arthur Nádas
IEEE Transactions on Neural Networks