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Conference Paper: Generalized Sorting with Predictions Revisited

TitleGeneralized Sorting with Predictions Revisited
Authors
KeywordsForbidden Comparison
Generalized Sorting
Predictions
Issue Date26-Aug-2023
PublisherSpringer
Abstract

This paper presents a novel algorithm for the generalized sorting problem with predictions, which involves determining a total ordering of an underlying directed graph using as few probes as possible. Specifically, we consider the problem of sorting an undirected graph with predicted edge directions. Our proposed algorithm is a Monte Carlo approach that has a polynomial-time complexity, which uses �(�log⁡�+�) probes with probability at least 1−�−Θ(�), where n is the number of vertices in the graph and w is the number of mispredicted edges. Our approach involves partitioning the vertices of the graph into O(w) disjoint verified directed paths, which can reduce the number of probes required. Lu et al. [11] introduced a bound of �(�log⁡�+�) for the number of probes, which was the only known result in this setting. Our bound reduces the factor �(log⁡�) to �(log⁡�).


Persistent Identifierhttp://hdl.handle.net/10722/338129

 

DC FieldValueLanguage
dc.contributor.authorChan, TH-
dc.contributor.authorSun, E-
dc.contributor.authorWang, B -
dc.date.accessioned2024-03-11T10:26:28Z-
dc.date.available2024-03-11T10:26:28Z-
dc.date.issued2023-08-26-
dc.identifier.urihttp://hdl.handle.net/10722/338129-
dc.description.abstract<p>This paper presents a novel algorithm for the generalized sorting problem with predictions, which involves determining a total ordering of an underlying directed graph using as few probes as possible. Specifically, we consider the problem of sorting an undirected graph with predicted edge directions. Our proposed algorithm is a Monte Carlo approach that has a polynomial-time complexity, which uses �(�log⁡�+�) probes with probability at least 1−�−Θ(�), where <em>n</em> is the number of vertices in the graph and <em>w</em> is the number of mispredicted edges. Our approach involves partitioning the vertices of the graph into <em>O</em>(<em>w</em>) disjoint verified directed paths, which can reduce the number of probes required. Lu et al. [<a title="Lu, P., Ren, X., Sun, E., Zhang, Y.: Generalized sorting with predictions. In: SOSA, pp. 111–117. SIAM (2021)" href="https://link.springer.com/chapter/10.1007/978-3-031-39344-0_3#ref-CR11">11</a>] introduced a bound of �(�log⁡�+�) for the number of probes, which was the only known result in this setting. Our bound reduces the factor �(log⁡�) to �(log⁡�).<br></p>-
dc.languageeng-
dc.publisherSpringer-
dc.relation.ispartofFrontier of Algorithmic Wisdom - International Joint Conference, IJTCS-FAW 2023 (14/08/2023-18/08/2023, Macau)-
dc.subjectForbidden Comparison-
dc.subjectGeneralized Sorting-
dc.subjectPredictions-
dc.titleGeneralized Sorting with Predictions Revisited-
dc.typeConference_Paper-
dc.identifier.doi10.1007/978-3-031-39344-0_3-
dc.identifier.scopuseid_2-s2.0-85171456835-
dc.identifier.volume13933-
dc.identifier.spage29-
dc.identifier.epage41-

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