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of 18
pro vyhledávání: '"Sen, Sayantan"'
We initiate the study of quantum property testing in sparse directed graphs, and more particularly in the unidirectional model, where the algorithm is allowed to query only the outgoing edges of a vertex. In the classical unidirectional model the pro
Externí odkaz:
http://arxiv.org/abs/2410.05001
Triangle counting and sampling are two fundamental problems for streaming algorithms. Arguably, designing sampling algorithms is more challenging than their counting variants. It may be noted that triangle counting has received far greater attention
Externí odkaz:
http://arxiv.org/abs/2405.10167
Autor:
Bhattacharyya, Arnab, Gayen, Sutanu, John, Philips George, Sen, Sayantan, Vinodchandran, N. V.
This work establishes a novel link between the problem of PAC-learning high-dimensional graphical models and the task of (efficient) counting and sampling of graph structures, using an online learning framework. We observe that if we apply the expone
Externí odkaz:
http://arxiv.org/abs/2405.07914
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 find. Recently, in a series of works, testers like $\mathsf{Barbarik}$,
Externí odkaz:
http://arxiv.org/abs/2312.10999
Publikováno v:
Quantum 7, 1202 (2023)
We describe a simple algorithm for estimating the $k$-th normalized Betti number of a simplicial complex over $n$ elements using the path integral Monte Carlo method. For a general simplicial complex, the running time of our algorithm is $n^{O\left(\
Externí odkaz:
http://arxiv.org/abs/2211.09618
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 Computer Science. The original distribution testing model relies on samples d
Externí odkaz:
http://arxiv.org/abs/2207.12514
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 the non-tolerant version of bipartite testing has been extensively stu
Externí odkaz:
http://arxiv.org/abs/2204.12397
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 drawn samples from an oracle. The testing task is to distinguish a dis
Externí odkaz:
http://arxiv.org/abs/2110.09972
We design an algorithm for approximating the size of \emph{Max Cut} in dense graphs. Given a proximity parameter $\varepsilon \in (0,1)$, our algorithm approximates the size of \emph{Max Cut} of a graph $G$ with $n$ vertices, within an additive error
Externí odkaz:
http://arxiv.org/abs/2110.04574
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