VLDB 2026 Research / reviewers in the wild / expert
Matthias Lutter
dblp:195/8214
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2 · 1 since 2021Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Learning residual alternating automata
Sebastian Berndt 0001, Maciej Liskiewicz, Matthias Lutter, Rüdiger Reischuk |
Inf. Comput. | 3 |
| 2019 | Proper learning of k-term DNF formulas from satisfying assignments
Maciej Liskiewicz, Matthias Lutter, Rüdiger Reischuk |
J. Comput. Syst. Sci. | 2 |
| 2017 | Learning Residual Alternating AutomataabstractResiduality plays an essential role for learning finite automata. While residual deterministic and non-deterministic automata have been understood quite well, fundamental questions concerning alternating automata (AFA) remain open. Recently, Angluin, Eisenstat, and Fisman (2015) have initiated a systematic study of residual AFAs and proposed an algorithm called AL* – an extension of the popular L* algorithm – to learn AFAs. Based on computer experiments they have conjectured that AL* produces residual AFAs, but have not been able to give a proof. In this paper we disprove this conjecture by constructing a counterexample. As our main positive result we design an efficient learning algorithm, named AL** and give a proof that it outputs residual AFAs only. In addition, we investigate the succinctness of these different FA types in more detail. Sebastian Berndt 0001, Maciej Liskiewicz, Matthias Lutter, Rüdiger Reischuk |
AAAI | 3 |