Journal Articles by E. Angriman
E. Angriman,
A. van der Grinten,
M. von Looz,
H. Meyerhenke,
M. Nöllenburg,
M. Predari, and
C. Tzovas
Guidelines for Experimental Algorithmics: A Case Study in Network Analysis
Algorithms,
12(7),
2019
DOI,
RIS,
BibTex
E. Angriman,
A. van der Grinten,
M. von Looz,
H. Meyerhenke,
M. Nöllenburg,
M. Predari, and
C. Tzovas
Guidelines for Experimental Algorithmics in Network Analysis
CoRR,
190404690,
2019
arXiv eprint,
RIS,
BibTex
Conference Papers
E. Angriman,
H. Meyerhenke,
C. Schulz, and
B. Uçar
Fully-dynamic Weighted Matching Approximation in Practice
Proceedings of the 2021 {SIAM} Conference on Applied and Computational Discrete Algorithms, {ACDA} 2021, Virtual Conference, July 19-21, 2021,
SIAM,
2021
DOI,
RIS,
BibTex
E. Angriman,
R. Becker,
G. D'Angelo,
H. Gilbert,
A. van der Grinten, and
H. Meyerhenke
Group-Harmonic and Group-Closeness Maximization - Approximation and Engineering
Proceedings of the Symposium on Algorithm Engineering and Experiments, {ALENEX} 2021, Virtual Conference, January 10-11, 2021,
SIAM,
2021
DOI,
RIS,
BibTex
A. van der Grinten,
E. Angriman,
M. Predari, and
H. Meyerhenke
New Approximation Algorithms for Forest Closeness Centrality - for Individual Vertices and Vertex Groups
Proceedings of the 2021 {SIAM} International Conference on Data Mining, {SDM} 2021, Virtual Event, April 29 - May 1, 2021,
SIAM,
2021
DOI,
RIS,
BibTex
E. Angriman,
H. Meyerhenke,
C. Schulz, and
B. Uçar
Fully-dynamic Weighted Matching Approximation in Practice
Proceedings of the 2021 {SIAM} Conference on Applied and Computational Discrete Algorithms, {ACDA} 2021, Virtual Conference, July 19-21, 2021,
SIAM,
2021
DOI,
RIS,
BibTex
E. Angriman,
M. Predari,
A. van der Grinten, and
H. Meyerhenke
Approximation of the Diagonal of a Laplacian's Pseudoinverse for Complex Network Analysis
28th Annual European Symposium on Algorithms, ESA 2020, September 7-9, 2020, Pisa, Italy (Virtual Conference),
Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2020
DOI,
RIS,
BibTex
E. Angriman,
A. van der Grinten,
A. Bojchevski,
D. Zügner,
S. Günnemann, and
H. Meyerhenke
Group Centrality Maximization for Large-scale Graphs
Proceedings of the Symposium on Algorithm Engineering and Experiments, ALENEX 2020, Salt Lake City, UT, USA, January 5-6, 2020,
SIAM,
2020
DOI,
RIS,
BibTex
A. van der Grinten,
E. Angriman, and
H. Meyerhenke
Parallel Adaptive Sampling with Almost No Synchronization
Euro-Par 2019: Parallel Processing - 25th International Conference on Parallel and Distributed Computing, Göttingen, Germany, August 26-30, 2019, Proceedings,
Springer,
2019
DOI,
RIS,
BibTex
E. Angriman,
A. van der Grinten, and
H. Meyerhenke
Local Search for Group Closeness Maximization on Big Graphs
2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, December 9-12, 2019,
IEEE,
2019
DOI,
RIS,
BibTex
P. Bisenius,
E. Bergamini,
E. Angriman, and
H. Meyerhenke
Computing Top-k Closeness Centrality in Fully-dynamic Graphs
Proceedings of the Twentieth Workshop on Algorithm Engineering and Experiments, ALENEX 2018, New Orleans, LA, USA, January 7-8, 2018.,
2018
DOI,
RIS,
BibTex