EDBT 2026 Demo / reviewers in the wild / expert
Luke Hinde
dblp:196/2490
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 4
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% Automated reasoning and model checking · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity › proof complexity
frege systems |
0.4 | 1 | 2019 | Characterising tree-like Frege proofs for QBF · Inf. Comput. 2019 |
Computational complexity
proof complexity |
0.4 | 1 | 2019 | Characterising tree-like Frege proofs for QBF · Inf. Comput. 2019 |
Automated reasoning and model checking › satisfiability
quantified boolean formula |
0.4 | 1 | 2019 | Characterising tree-like Frege proofs for QBF · Inf. Comput. 2019 |
Methods — techniques the papers use, named apart from their topics
proof theory · 0.4frege systems · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Characterising tree-like Frege proofs for QBF
Olaf Beyersdorff, Luke Hinde |
Inf. Comput. | 2 |
| 2019 | Size, Cost, and Capacity: A Semantic Technique for Hard Random QBFsabstractAs a natural extension of the SAT problem, an array of proof systems for quantified Boolean formulas (QBF) have been proposed, many of which extend a propositional proof system to handle universal quantification. By formalising the construction of the QBF proof system obtained from a propositional proof system by adding universal reduction (Beyersdorff, Bonacina & Chew, ITCS `16), we present a new technique for proving proof-size lower bounds in these systems. The technique relies only on two semantic measures: the cost of a QBF, and the capacity of a proof. By examining the capacity of proofs in several QBF systems, we are able to use the technique to obtain lower bounds based on cost alone. As applications of the technique, we first prove exponential lower bounds for a new family of simple QBFs representing equality. The main application is in proving exponential lower bounds with high probability for a class of randomly generated QBFs, the first `genuine' lower bounds of this kind, which apply to the QBF analogues of resolution, Cutting Planes, and Polynomial Calculus. Finally, we employ the technique to give a simple proof of hardness for the prominent formulas of Kleine B\"uning, Karpinski and Fl\"ogel. Olaf Beyersdorff, Joshua Blinkhorn, Luke Hinde |
Log. Methods Comput. Sci. | 3 |
| 2018 | Size, Cost and Capacity: A Semantic Technique for Hard Random QBFsabstractAs a natural extension of the SAT problem, an array of proof systems for quantified Boolean formulas (QBF) have been proposed, many of which extend a propositional proof system to handle universal quantification. By formalising the construction of the QBF proof system obtained from a propositional proof system by adding universal reduction (Beyersdorff, Bonacina & Chew, ITCS'16), we present a new technique for proving proof-size lower bounds in these systems. The technique relies only on two semantic measures: the cost of a QBF, and the capacity of a proof. By examining the capacity of proofs in several QBF systems, we are able to use the technique to obtain lower bounds based on cost alone. As applications of the technique, we first prove exponential lower bounds for a new family of simple QBFs representing equality. The main application is in proving exponential lower bounds with high probability for a class of randomly generated QBFs, the first 'genuine' lower bounds of this kind, which apply to the QBF analogues of resolution, Cutting Planes, and Polynomial Calculus. Finally, we employ the technique to give a simple proof of hardness for a prominent family of QBFs. Olaf Beyersdorff, Joshua Blinkhorn, Luke Hinde |
ITCS | 3 |
| 2017 | Reasons for Hardness in QBF Proof SystemsabstractWe aim to understand inherent reasons for lower bounds for QBF proof systems, and revisit and compare two previous approaches in this direction. The first of these relates size lower bounds for strong QBF Frege systems to circuit lower bounds via strategy extraction (Beyersdorff & Pich, LICS'16). Here we show a refined version of strategy extraction and thereby for any QBF proof system obtain a trichotomy for hardness: (1) via circuit lower bounds, (2) via propositional Resolution lower bounds, or (3) `genuine' QBF lower bounds. The second approach tries to explain QBF lower bounds through quantifier alternations in a system called relaxing QU-Res (Chen, ICALP'16). We prove a strong lower bound for relaxing QU-Res, which also exhibits significant shortcomings of that model. Prompted by this we propose an alternative, improved version, allowing more flexible oracle queries in proofs. We show that lower bounds in our new model correspond to the trichotomy obtained via strategy extraction. Olaf Beyersdorff, Luke Hinde, Ján Pich |
FSTTCS | 2 |