Demo Data from VLDB 2026 / reviewers in the wild / expert
Gábor Galambos
dblp:62/3370
· DBLP profile ↗
9ranked-venue papers
2as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 8 · 2 first-authorSystems, architecture and hardware · 1Databases, data management, data science and information retrieval · 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
3 papers |
Approximation and online algorithms · 65% Computational complexity · 19% Mathematical optimization · 16% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Electronic design automation · 67% Parallel and multicore computing · 33% |
Topics — the 12 heaviest of 12, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Approximation and online algorithms › online algorithms
competitive analysis |
0.1 | 2 | 2008 | Lower Bound for the Online Bin Packing Problem with Restricted Repacking · SIAM J. Comput. 2008 A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling" · SIAM J. Comput. 1997 |
Approximation and online algorithms
bin packing |
0.1 | 1 | 2008 | Lower Bound for the Online Bin Packing Problem with Restricted Repacking · SIAM J. Comput. 2008 |
Computational complexity
lower bounds |
0.1 | 1 | 2008 | Lower Bound for the Online Bin Packing Problem with Restricted Repacking · SIAM J. Comput. 2008 |
Approximation and online algorithms
online algorithms |
0.1 | 1 | 2008 | Lower Bound for the Online Bin Packing Problem with Restricted Repacking · SIAM J. Comput. 2008 |
Mathematical optimization › scheduling
list scheduling |
0.0 | 2 | 1997 | A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling" · SIAM J. Comput. 1997 An On-Line Scheduling Heuristic With Better Worst Case Ratio Than Graham's List Scheduling · SIAM J. Comput. 1993 |
Approximation and online algorithms › online algorithms
online scheduling |
0.0 | 2 | 1997 | A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling" · SIAM J. Comput. 1997 An On-Line Scheduling Heuristic With Better Worst Case Ratio Than Graham's List Scheduling · SIAM J. Comput. 1993 |
Mathematical optimization
discrete optimization |
0.0 | 1 | 2008 | Lower Bound for the Online Bin Packing Problem with Restricted Repacking · SIAM J. Comput. 2008 |
Mathematical optimization › scheduling › completion time minimization
makespan minimization |
0.0 | 1 | 1997 | A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling" · SIAM J. Comput. 1997 |
Electronic design automation › high-level synthesis › scheduling
makespan minimization |
0.0 | 1 | 1993 | An On-Line Scheduling Heuristic With Better Worst Case Ratio Than Graham's List Scheduling · SIAM J. Comput. 1993 |
Parallel and multicore computing › task scheduling
online scheduling |
0.0 | 1 | 1993 | An On-Line Scheduling Heuristic With Better Worst Case Ratio Than Graham's List Scheduling · SIAM J. Comput. 1993 |
Electronic design automation › high-level synthesis
scheduling |
0.0 | 1 | 1993 | An On-Line Scheduling Heuristic With Better Worst Case Ratio Than Graham's List Scheduling · SIAM J. Comput. 1993 |
Approximation and online algorithms › approximation algorithms › approximation guarantees
worst-case ratio |
0.0 | 1 | 1997 | A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling" · SIAM J. Comput. 1997 |
Methods — techniques the papers use, named apart from their topics
optimization problem analysis · 0.1lower bound proof · 0.1worst-case ratio analysis · 0.0competitive analysis · 0.0combinatorial analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Matrix transpose on meshes with buses
József Békési, Gábor Galambos |
J. Parallel Distributed Comput. | 2 |
| 2012 | New lower bounds for certain classes of bin packing algorithms
János Balogh, József Békési, Gábor Galambos |
Theor. Comput. Sci. | 3 |
| 2010 | New Lower Bounds for Certain Classes of Bin Packing Algorithms
János Balogh, József Békési, Gábor Galambos |
WAOA | 3 |
| 2008 | Lower Bound for the Online Bin Packing Problem with Restricted RepackingabstractIn 1996 Ivkovič and Lloyd [A fundamental restriction on fully dynamic maintenance of bin packing, Inform. Process. Lett., 59 (1996), pp. 229–232] gave the lower bound $\frac{4}{3}$ on the asymptotic worst-case ratio for so-called fully dynamic bin packing algorithms, where the number of repackable items in each step is restricted by a constant. In this paper we improve this result to about $1.3871$. We present our proof for a semionline case of the classical bin packing, but it works for fully dynamic bin packing as well. We prove the lower bound by analyzing and solving a specific optimization problem. The bound can be expressed exactly using the Lambert W function. János Balogh, József Békési, Gábor Galambos, Gerhard Reinelt |
SIAM J. Comput. | 3 |
| 2001 | Worst-case analysis of the Iterated Longest Fragment algorithm
József Békési, Gábor Galambos |
Inf. Process. Lett. | 2 |
| 2000 | A 5/4 Linear Time Bin Packing Algorithm
József Békési, Gábor Galambos, Hans Kellerer |
J. Comput. Syst. Sci. | 2 |
| 1997 | A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling"abstractPrevious article A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling"R. Chandrasekaran, Bo Chen, Gábor Galambos, P. R. Narayanan, André Van Vliet, and Gerhard J. WoegingerR. Chandrasekaran, Bo Chen, Gábor Galambos, P. R. Narayanan, André Van Vliet, and Gerhard J. Woegingerhttps://doi.org/10.1137/S0097539793258775PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] Google Scholar[2] Gábor Galambos and , Gerhard Woeginger, An on‐line scheduling heuristic with better worst‐case ratio than Graham’s list scheduling, SIAM J. Comput., 22 (1993), 349–355 94b:90031 LinkISIGoogle Scholar[3] Google ScholarKeywordscombinatorial problemsschedulingworst-case boundson-line algorithms Previous article FiguresRelatedReferencesCited ByDetails A survey on makespan minimization in semi-online environmentsJournal of Scheduling, Vol. 21, No. 3 | 13 April 2018 Cross Ref Scheduling Web Advertisements: A Note on the Minspace ProblemJournal of Scheduling, Vol. 8, No. 1 | 1 Jan 2005 Cross Ref On-line scheduling revisitedJournal of Scheduling, Vol. 3, No. 6 | 1 January 2000 Cross Ref Online Scheduling RevisitedAlgorithms - ESA 2000 | 11 February 2003 Cross Ref A Review of Machine Scheduling: Complexity, Algorithms and ApproximabilityHandbook of Combinatorial Optimization | 1 Jan 1998 Cross Ref Volume 26, Issue 3| 1997SIAM Journal on Computing605-872 History Published online:28 July 2006 InformationCopyright © 1997 Society for Industrial and Applied MathematicsKeywordscombinatorial problemsschedulingworst-case boundson-line algorithmsMSC codes90B3590C27PDF Download Article & Publication DataArticle DOI:10.1137/S0097539793258775Article page range:pp. 870-872ISSN (print):0097-5397ISSN (online):1095-7111Publisher:Society for Industrial and Applied Mathematics Ramaswamy Chandrasekaran, Bo Chen 0002, Gábor Galambos, P. R. Narayanan, André van Vliet |
SIAM J. Comput. | 3 |
| 1993 | A Simple Proof of Liang's Lower Bound for On-Line bin Packing and the Extension to the Parametric Case
Gábor Galambos, J. B. G. Frenk |
Discret. Appl. Math. | 1 |
| 1993 | An On-Line Scheduling Heuristic With Better Worst Case Ratio Than Graham's List SchedulingabstractThe problem of on-line scheduling a set of independent jobs on m machines is considered. The goal is to minimize the makespan of the schedule. Graham’s List Scheduling heuristic [R. L. Graham, SIAM J. Appl. Math., 17(1969), pp. 416–429] guarantees a worst case performance of $2 - \frac{1} {m}$ for this problem. This worst case bound cannot be improved for $m = 2$ and $m = 3$. For $m \geqslant 4$, approximation algorithms with worst case performance at most $2 - \frac{1}{m} - \varepsilon _m $ are presented, where $\varepsilon _m $ is some positive real depending only on m. Gábor Galambos, Gerhard J. Woeginger |
SIAM J. Comput. | 1 |