most citedOn Estimating Maximum Matching Size in Graph Streams

65 citations · 66 across the 4 of their papers we have counts for

collaborators

7 papers

cs.DS20231 cited

Hidden Permutations to the Rescue: Multi-Pass Semi-Streaming Lower Bounds for Approximate Matchings

Sepehr Assadi, Janani Sundaresan

We prove that any semi-streaming algorithm for -approximation of maximum bipartite matching requires \[ Ω(\frac{\log{(1/ε)}}{\log{(1/β)}}) \] passes, where is t…

cs.DS2023

(Noisy) Gap Cycle Counting Strikes Back: Random Order Streaming Lower Bounds for Connected Components and Beyond

Sepehr Assadi, Janani Sundaresan

We continue the study of the communication complexity of gap cycle counting problems. These problems have been introduced by Verbin and Yu [SODA 2011] and have found numerous appli…

cs.DS2023

Generalizing Greenwald-Khanna Streaming Quantile Summaries for Weighted Inputs

Sepehr Assadi, Nirmit Joshi, Milind Prabhu +1

Estimating quantiles, like the median or percentiles, is a fundamental task in data mining and data science. A (streaming) quantile summary is a data structure that can process a s…

cs.DS2022

Tight Bounds for Monotone Minimal Perfect Hashing

Sepehr Assadi, Martin Farach-Colton, William Kuszmaul

The monotone minimal perfect hash function (MMPHF) problem is the following indexing problem. Given a set of distinct keys from a universe of size $…

cs.DS2022

On Regularity Lemma and Barriers in Streaming and Dynamic Matching

Sepehr Assadi, Soheil Behnezhad, Sanjeev Khanna +1

We present a new approach for finding matchings in dense graphs by building on Szemerédi's celebrated Regularity Lemma. This allows us to obtain non-trivial albeit slight improveme…

cs.DS20221 cited

Decremental Matching in General Graphs

Sepehr Assadi, Aaron Bernstein, Aditi Dudeja

We consider the problem of maintaining an approximate maximum integral matching in a dynamic graph , while the adversary makes changes to the edges of the graph. The goal is to…