Demo Data from EDBT 2026 / reviewers in the wild / expert
Alex Krimkevitch
dblp:41/9509
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
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 |
Computational complexity · 67% Logic in computer science · 33% | |
| Artificial intelligence
1 paper |
Knowledge representation and reasoning · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity
constraint satisfaction |
0.1 | 1 | 2011 | Tractable Set Constraints · IJCAI 2011 |
Logic in computer science › program analysis
set constraints |
0.1 | 1 | 2011 | Tractable Set Constraints · IJCAI 2011 |
Computational complexity › constraint satisfaction › complexity classification
tractable constraint languages |
0.1 | 1 | 2011 | Tractable Set Constraints · IJCAI 2011 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
description logic |
0.0 | 1 | 2011 | Tractable Set Constraints · IJCAI 2011 |
Methods — techniques the papers use, named apart from their topics
universal algebra · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Tractable Set ConstraintsabstractMany fundamental problems in artificial intelligence, knowledge representation, and verification involve reasoning about sets and relations between sets and can be modeled as set constraint satisfaction problems (set CSPs). Such problems are frequently intractable, but there are several important set CSPs that are known to be polynomial-time tractable. We introduce a large class of set CSPs that can be solved in quadratic time. Our class, which we call EI, contains all previously known tractable set CSPs, but also some new ones that are of crucial importance for example in description logics. The class of EI set constraints has an elegant universal-algebraic characterization, which we use to show that every set constraint language that properly contains all EI set constraints already has a finite sublanguage with an NP-hard constraint satisfaction problem. Manuel Bodirsky, Martin Hils, Alex Krimkevitch |
IJCAI | 3 |