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From the 1 of 48 linked papers with an AI index.

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20242026
most citedRedundancy Is All You Need (for CSP Sparsification)

1 citations · 1 across the 15 of their papers we have counts for

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cs.DS2026

Inapproximability of Unique-Machine Precedence Scheduling for Unit-Length Jobs

Venkatesan Guruswami, Xuandi Ren, Shaoxuan Tang

The paper shows that scheduling unit-length jobs with unique-machine precedence constraints cannot be approximated within any constant factor, and under standard complexity assumpt…

cs.DS20261 cited

Redundancy Is All You Need (for CSP Sparsification)

Joshua Brakensiek, Venkatesan Guruswami

The seminal work of Benczúr and Karger demonstrated cut sparsifiers of near-linear size. Subsequent extensions have yielded sparsifiers for hypergraph cuts and more recently linea…

cs.DS2026

New Algorithms and Hardness Results for Robust Satisfiability of (Promise) CSPs

Joshua Brakensiek, Lorenzo Ciardo, Venkatesan Guruswami +2

In this paper, we continue the study of robust satisfiability of promise CSPs (PCSPs), initiated in (Brakensiek, Guruswami, Sandeep, STOC 2023 / Discrete Analysis 2025), and obtain…

cs.DS2026

Tight Bounds for Sparsifying Random CSPs

Joshua Brakensiek, Venkatesan Guruswami, Aaron Putterman

The problem of CSP sparsification asks: for a given CSP instance, what is the sparsest possible reweighting such that for every possible assignment to the instance, the number of s…

cs.DS2025

Scheduling Problems with Constrained Rejections

Sami Davies, Venkatesan Guruswami, Xuandi Ren

We study bicriteria versions of Makespan Minimization on Unrelated Machines and Santa Claus by allowing a constrained number of rejections. Given an instance of Makespan Minimizati…

cs.DS2025

SDPs and Robust Satisfiability of Promise CSP

Joshua Brakensiek, Venkatesan Guruswami, Sai Sandeep

For a constraint satisfaction problem (CSP), a robust satisfaction algorithm is one that outputs an assignment satisfying most of the constraints on instances that are near-satisfi…