Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from VLDB 2026 / reviewers in the wild / expert

Michal Stawarz

dblp:420/9039 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none

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

Theory of computation · 1 · 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
Graph algorithms and graph theory · 33% Approximation and online algorithms · 33% Computational complexity · 33%

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

TopicWeightPapersLastEvidence papers
Approximation and online algorithms › approximation algorithms › approximation guarantees
additive approximation		 1.012026
Improved Additive Approximation Algorithms for APSP · SODA 2026
Graph algorithms and graph theory › shortest path
all-pairs shortest paths		 1.012026
Improved Additive Approximation Algorithms for APSP · SODA 2026
Computational complexity › algebraic complexity › matrix multiplication
fast matrix multiplication		 1.012026
Improved Additive Approximation Algorithms for APSP · SODA 2026

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

algebraic techniques · 1.0
YearPublicationVenuePosition
2026 Improved Additive Approximation Algorithms for APSP
abstract
The All-Pairs Shortest Paths (APSP) is a foundational problem in theoretical computer science. Approximating APSP in undirected unweighted graphs has been studied for many years, beginning with the work of Dor, Halperin and Zwick [SICOMP’01]. Many recent works have attempted to improve these original algorithms using the algebraic tools of fast matrix multiplication. We improve on these results for the following problems.
Ce Jin 0001, Yael Kirkpatrick, Michal Stawarz, Virginia Vassilevska Williams
 SODA3