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Ruxi Shi

dblp:322/8078 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0001-7696-4787ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Information theory · 67% Mathematical optimization · 33%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information theory › information measures
entropy		 0.612022
On Variational Principles for Metric Mean Dimension · IEEE Trans. Inf. Theory 2022
Information theory › ergodic theory
metric mean dimension		 0.612022
On Variational Principles for Metric Mean Dimension · IEEE Trans. Inf. Theory 2022
Mathematical optimization › variational analysis
variational principle		 0.612022
On Variational Principles for Metric Mean Dimension · IEEE Trans. Inf. Theory 2022

Methods — techniques the papers use, named apart from their topics

shapira entropy · 0.6brin-katok local entropy · 0.6
YearPublicationVenuePosition
2022 On Variational Principles for Metric Mean Dimension
abstract
In this note, we show several variational principles for metric mean dimension. First we prove a variational principles in terms of Shapira’s entropy related to finite open covers. Second we establish a variational principle in terms of Katok’s entropy. Finally using these two variational principles we develop a variational principle in terms of Brin-Katok local entropy.
Ruxi Shi
 IEEE Trans. Inf. Theory1