Demo Data from EDBT 2026 / reviewers in the wild / expert
Gerhard Rauchecker
dblp:150/8111
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Security and privacy · 1 · 1 first-authorGraphics, 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 |
Algorithmic game theory and mechanism design · 77% Mathematical optimization · 23% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › fair division › fair-division mechanisms
approximation algorithms for fair division |
0.3 | 1 | 2017 | Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017 |
Algorithmic game theory and mechanism design
fair division |
0.3 | 1 | 2017 | Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017 |
Algorithmic game theory and mechanism design › fair division
indivisible chores allocation |
0.3 | 1 | 2017 | Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017 |
Mathematical optimization
discrete optimization |
0.1 | 1 | 2017 | Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017 |
Mathematical optimization › scheduling
parallel machine scheduling |
0.1 | 1 | 2017 | Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017 |
Mathematical optimization
scheduling |
0.1 | 1 | 2017 | Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017 |
Methods — techniques the papers use, named apart from their topics
polynomial-time approximation scheme · 0.3approximation algorithm · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Algorithms for Max-Min Share Fair Allocation of Indivisible ChoresabstractWe consider Max-min Share (MmS) fair allocations of indivisible chores (items with negative utilities). We show that allocation of chores and classical allocation of goods (items with positive utilities) have some fundamental connections but also differences which prevent a straightforward application of algorithms for goods in the chores setting and vice-versa. We prove that an MmS allocation does not need to exist for chores and computing an MmS allocation - if it exists - is strongly NP-hard. In view of these non-existence and complexity results, we present a polynomial-time 2-approximation algorithm for MmS fairness for chores. We then introduce a new fairness concept called optimal MmS that represents the best possible allocation in terms of MmS that is guaranteed to exist. We use connections to parallel machine scheduling to give (1) a polynomial-time approximation scheme for computing an optimal MmS allocation when the number of agents is fixed and (2) an effective and efficient heuristic with an ex-post worst-case analysis. Haris Aziz 0001, Gerhard Rauchecker, Guido Schryen, Toby Walsh |
AAAI | 2 |
| 2014 | A Decision Support System for IT Security Incident Management
Gerhard Rauchecker, Emrah Yasasin, Guido Schryen |
TrustBus | 1 |