Skip to content
AI Atlas
Papercs.LG

Selecting k Paths with the Minimum Longest Path Length in the Stochastic Semi-Bandit Setting

Published 15 Sept 2026arXiv:2609.14557

data quality89

Updated 29 h ago · first seen 15 Sept 2026

paper_01M2JK0BWQF2XPYVZ2KYHSDS37

Abstract

When performing parallel data transmission through a network using multiple paths, it is practically important to minimize the maximum transmission time among the selected paths. This study addresses an online problem in which $k$ paths from an origin vertex to a destination vertex must be selected at each time step within a network represented as a directed graph. Here, the number of paths going through each edge in each parallel data transmission is limited to its capacity, and the time required for transmission is determined stochastically. We formulate the semi-bandit problem of selecting a set of paths to minimize the maximum traversal time among the selected paths and propose an algorithm to solve it.

Authors

Authors 2

Atsuyoshi NakamuraShunsuke Aoki

Linked names open researcher pages (created from the paper's author list; name-only, no affiliation unless a source states it). Unlinked names have no researcher record yet.

Organizations

Organizations 0

No organization stated. arXiv metadata does not carry affiliations; an organization is linked only when a model card or lab page cites the paper.

Models

Models introduced or described 0

Inbound described_by relations from model cards and documentation.

No model links this paper yet

Model pages link papers through their model cards and documentation; the relation is written only when a source states it.

Datasets

Datasets used 0

No dataset relation recorded.

Benchmarks

Benchmarks used 0

No benchmark relation recorded.

Code

Repositories & frameworks 0

No repository linked.

Timeline

Timeline 1

Full timeline →

Sources

Sources 1

Source documents
SourceDocumentTypeTierLast observedSnapshots
arXiv (Atom API + RSS)rss.arxiv.org/rss/cs.LG feedT1· Official21 h ago3

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.