Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Gerhard Rauchecker

dblp:150/8111 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › fair division › fair-division mechanisms
approximation algorithms for fair division
0.312017
Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017
Algorithmic game theory and mechanism design
fair division
0.312017
Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017
Algorithmic game theory and mechanism design › fair division
indivisible chores allocation
0.312017
Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017
Mathematical optimization
discrete optimization
0.112017
Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017
Mathematical optimization › scheduling
parallel machine scheduling
0.112017
Algorithms for Max-Min Share Fair Allocation of Indivisible Chores · AAAI 2017
Mathematical optimization
scheduling
0.112017
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
YearPublicationVenuePosition
2017 Algorithms for Max-Min Share Fair Allocation of Indivisible Chores
abstract
We 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
AAAI2
2014 A Decision Support System for IT Security Incident Management
Gerhard Rauchecker, Emrah Yasasin, Guido Schryen
TrustBus1