2 citations · 4 across the 4 of their papers we have counts for
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cs.DS2021
-norm Flow Diffusion in Near-Linear Time
Li Chen, Richard Peng, Di Wang
Diffusion is a fundamental graph procedure and has been a basic building block in a wide range of theoretical and empirical applications such as graph partitioning and semi-supervi…
cs.DS2019★ 2 cited
Flowless: Extracting Densest Subgraphs Without Flow Computations
Digvijay Boob, Yu Gao, Richard Peng +4
We propose a simple and computationally efficient method for dense subgraph discovery, which is a classic problem both in theory and in practice. It is well known that dense subgra…
cs.DS2019
Flows in Almost Linear Time via Adaptive Preconditioning
Rasmus Kyng, Richard Peng, Sushant Sachdeva +1
We present algorithms for solving a large class of flow and regression problems on unit weighted graphs to accuracy in almost-linear time. These problems includ…