Algorithmic Efficiency via Instance-Optimal Understanding (AEIOU)
Public support
Provider
Czech Science Foundation
Programme
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Call for proposals
SGA0202600003
Main participants
Univerzita Karlova / Matematicko-fyzikální fakulta
Contest type
VS - Public tender
Contract ID
26-23599M
Alternative language
Project name in Czech
Algorithmic Efficiency via Instance-Optimal Understanding (AEIOU)
Annotation in Czech
Our research focuses on instance optimality, a framework that extends classical worst-case and parameterized complexity by guaranteeing nearly optimal performance on every input. We aim to develop algorithms and data structures that achieve instance-optimal performance for fundamental problems in ordering, sampling, sublinear, and distributed algorithms. Recent results have shown that this approach provides a valuable perspective for addressing problems in theoretical computer science. By refining and generalizing the notion of instance optimality, we hope to create a broadly applicable framework that advances both theoretical understanding and practical applications.
Scientific branches
R&D category
ZV - Basic research
OECD FORD - main branch
10102 - Applied mathematics
OECD FORD - secondary branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
OECD FORD - another secondary branch
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CEP - equivalent branches <br>(according to the <a href="http://www.vyzkum.cz/storage/att/E6EF7938F0E854BAE520AC119FB22E8D/Prevodnik_oboru_Frascati.pdf">converter</a>)
AF - Documentation, librarianship, work with information<br>BC - Theory and management systems<br>BD - Information theory<br>IN - Informatics
Solution timeline
Realization period - beginning
Jan 1, 2026
Realization period - end
Dec 31, 2030
Project status
Z - Beginning multi-year project
Latest support payment
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Data delivery to CEP
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data delivery code
CEP26-GA0-GM-R
Data delivery date
Apr 27, 2026
Finance
Total approved costs
23,265 thou. CZK
Public financial support
23,265 thou. CZK
Other public sources
0 thou. CZK
Non public and foreign sources
0 thou. CZK