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20212026
most citedA (simple) classical algorithm for estimating Betti numbers

9 citations · 12 across the 6 of their papers we have counts for

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10 papers · 1 filter

cs.DS2026

Private Graph Property Testing

Hendrik Fichtenberger, Abigail Gentle, Tamalika Mukherjee +1

Graph property testing asks whether a massive graph satisfies a given property, or is far from doing so, using only a sublinear number of queries to the graph. Since property teste…

cs.DS2025

Instance Dependent Testing of Samplers using Interval Conditioning

Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2

Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Pro…

cs.DS2024★ 1 cited

Testing vs Estimation for Index-Invariant Properties in the Huge Object Model

Sourav Chakraborty, Eldar Fischer, Arijit Ghosh +3

The Huge Object model of property testing [Goldreich and Ron, TheoretiCS 23] concerns properties of distributions supported on , where is so large that even reading…

cs.DS2024

Near Uniform Triangle Sampling Over Adjacency List Graph Streams

Arijit Bishnu, Arijit Ghosh, Gopinath Mishra +1

Triangle counting and sampling are two fundamental problems for streaming algorithms. Arguably, designing sampling algorithms is more challenging than their counting variants. It m…

cs.DS2023

Testing Self-Reducible Samplers

Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2

Samplers are the backbone of the implementations of any randomised algorithm. Unfortunately, obtaining an efficient algorithm to test the correctness of samplers is very hard to fi…

cs.DS2022★ 9 cited

A (simple) classical algorithm for estimating Betti numbers

Simon Apers, Sander Gribling, Sayantan Sen +1

We describe a simple algorithm for estimating the -th normalized Betti number of a simplicial complex over elements using the path integral Monte Carlo method. For a general…

cs.DS2022★ 2 cited

Testing of Index-Invariant Properties in the Huge Object Model

Sourav Chakraborty, Eldar Fischer, Arijit Ghosh +2

The study of distribution testing has become ubiquitous in the area of property testing, both for its theoretical appeal, as well as for its applications in other fields of Compute…

cs.DS2022

Tolerant Bipartiteness Testing in Dense Graphs

Arijit Ghosh, Gopinath Mishra, Rahul Raychaudhury +1

Bipartite testing has been a central problem in the area of property testing since its inception in the seminal work of Goldreich, Goldwasser and Ron [FOCS'96 and JACM'98]. Though…

cs.DS2021

Exploring the Gap between Tolerant and Non-tolerant Distribution Testing

Sourav Chakraborty, Eldar Fischer, Arijit Ghosh +2

The framework of distribution testing is currently ubiquitous in the field of property testing. In this model, the input is a probability distribution accessible via independently…

cs.DS2021

A Faster Algorithm for Max Cut in Dense Graphs

Arijit Ghosh, Gopinath Mishra, Rahul Raychaudhury +1

We design an algorithm for approximating the size of \emph{Max Cut} in dense graphs. Given a proximity parameter , our algorithm approximates the size of \em…