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ORCIDAnna Beer 0001
Person information
- affiliation: Aarhus University, Aarhus, Denmark
Other persons with the same name
- Anna Beer 0002
![[0000-0002-3447-0575]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-3447-0575")
— TIB - Leibniz Information Centre for Science and Technology, Hannover, Germany
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2020 – today
- 2024
[c25]Anna Beer, Olivér Palotás, Andrea Maldonado, Andrew Draganov, Ira Assent:
DROPP: Structure-Aware PCA for Ordered Data: A General Method and its Applications in Climate Research and Molecular Dynamics. ICDE 2024: 1143-1156- [c24]Philipp Jahn, Christian M. M. Frey, Anna Beer, Collin Leiber, Thomas Seidl:
Data with Density-Based Clusters: A Generator for Systematic Evaluation of Clustering Algorithms. ECML/PKDD (7) 2024: 3-21 - [c23]Sandra Gilhuber, Anna Beer, Yunpu Ma, Thomas Seidl:
FALCUN: A Simple and Efficient Deep Active Learning Strategy. ECML/PKDD (3) 2024: 421-439 - [i1]Anna Beer, Martin Heinrigs, Claudia Plant, Ira Assent:
Temporal Subspace Clustering for Molecular Dynamics Data. CoRR abs/2408.00056 (2024) - 2023
- [j3]Theresa Ullmann, Anna Beer, Maximilian Hünemörder, Thomas Seidl, Anne-Laure Boulesteix:
Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study. Adv. Data Anal. Classif. 17(1): 211-238 (2023) - [c22]Anna Beer, Andrew Draganov, Ellen Hohma, Philipp Jahn, Christian M. M. Frey, Ira Assent:
Connecting the Dots - Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering. KDD 2023: 80-92 - 2022
- [j2]Ellen Hohma, Christian M. M. Frey, Anna Beer, Thomas Seidl:
SCAR - Spectral Clustering Accelerated and Robustified. Proc. VLDB Endow. 15(11): 3031-3044 (2022) - 2021
- [b1]Anna Beer:
On the edges of clustering: creating synergies with related problems. Ludwig Maximilian University of Munich, Germany, 2021 - [c21]Sandra Obermeier, Anna Beer, Florian Wahl, Thomas Seidl:
Cluster Flow - an Advanced Concept for Ensemble-Enabling, Interactive Clustering. BTW 2021: 175-194 - [c20]Daniyal Kazempour, Anna Beer, Melanie Oelker, Peer Kröger, Thomas Seidl:
Compound Segmentation via Clustering on Mol2Vec-based Embeddings. e-Science 2021: 60-69 - [c19]Anna Beer, Ekaterina Allerborn, Valentin Hartmann, Thomas Seidl:
KISS - A fast kNN-based Importance Score for Subspaces. EDBT 2021: 391-396 - [c18]Anna Beer, Lisa Stephan, Thomas Seidl:
LUCKe - Connecting Clustering and Correlation Clustering. ICDM (Workshops) 2021: 431-440 - [c17]Andreas Lohrer, Anna Beer, Maximilian Archimedes Xaver Hünemörder, Jenny Lauterbach, Thomas Seidl, Peer Kröger:
AnyCORE - An Anytime Algorithm for Cluster Outlier REmoval. LWDA 2021: 145-156 - 2020
- [c16]Daniyal Kazempour, Anna Beer, Peer Kröger, Thomas Seidl:
I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering. ICDM (Workshops) 2020: 316-323 - [c15]Anna Beer, Daniyal Kazempour, Julian Busch, Alexander Tekles, Thomas Seidl:
Grace - Limiting the Number of Grid Cells for Clustering High-Dimensional Data. LWDA 2020: 11-22 - [c14]Anna Beer, Dominik Seeholzer, Nadine Sarah Schüler, Thomas Seidl:
Angle-Based Clustering. SISAP 2020: 312-320 - [c13]Anna Beer, Valentin Hartmann, Thomas Seidl:
Orderings of Data - More Than a Tripping Hazard: Visionary. SSDBM 2020: 17:1-17:4
2010 – 2019
- 2019
- [j1]Janis Held, Anna Beer, Thomas Seidl:
Chain-detection Between Clusters. Datenbank-Spektrum 19(3): 219-230 (2019) - [c12]Janis Held, Anna Beer, Thomas Seidl:
Chain-detection for DBSCAN. BTW (Workshops) 2019: 173-183 - [c11]Anna Beer, Daniyal Kazempour, Thomas Seidl:
Rock - Let the points roam to their clusters themselves. EDBT 2019: 630-633 - [c10]Anna Beer, Daniyal Kazempour, Marcel Baur, Thomas Seidl:
Human Learning in Data Science. HCI (34) 2019: 170-176 - [c9]Daniyal Kazempour, Anna Beer, Thomas Seidl:
Data on RAILs: On Interactive Generation of Artificial Linear Correlated Data. HCI (34) 2019: 184-189 - [c8]Anna Beer, Nadine Sarah Schüler, Thomas Seidl:
A Generator for Subspace Clusters. LWDA 2019: 69-73 - [c7]Maximilian Archimedes Xaver Hünemörder, Anna Beer, Daniyal Kazempour, Thomas Seidl:
CODEC - Detecting Linear Correlations in Dense Clusters using coMAD-based PCA. LWDA 2019: 111-114 - [c6]Daniyal Kazempour, Anna Beer, Oliver Schrüfer, Thomas Seidl:
Clustering Trend Data Time-Series through Segmentation of FFT-decomposed Signal Constituents. LWDA 2019: 127-138 - [c5]Anna Beer, Jennifer Lauterbach, Thomas Seidl:
MORe++: k-Means Based Outlier Removal on High-Dimensional Data. SISAP 2019: 188-202 - [c4]Anna Beer, Daniyal Kazempour, Lisa Stephan, Thomas Seidl:
LUCK- Linear Correlation Clustering Using Cluster Algorithms and a kNN based Distance Function. SSDBM 2019: 181-184 - [c3]Anna Beer, Thomas Seidl:
Graph Ordering and Clustering: A Circular Approach. SSDBM 2019: 185-188 - 2018
- [c2]Daniyal Kazempour, Anna Beer, Friederike Herzog, Daniel Kaltenthaler, Johannes-Y. Lohrer, Thomas Seidl:
FATBIRD: A Tool for Flight and Trajectories Analyses of Birds. eScience 2018: 75-82 - [c1]Daniyal Kazempour, Anna Beer, Johannes-Y. Lohrer, Daniel Kaltenthaler, Thomas Seidl:
PARADISO: an interactive approach of parameter selection for the mean shift algorithm. SSDBM 2018: 26:1-26:4
Coauthor Index
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