Structure-Preserving Difference Search for XML Documents. - Erich Schubert; Sebastian Schaffert; François Bry (Extreme Markup Languages®, 2005)

A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms. - Hans-Peter Kriegel; Peer Kröger; Erich Schubert; Arthur Zimek (SSDBM, 2008)

LoOP: local outlier probabilities. - Hans-Peter Kriegel; Peer Kröger; Erich Schubert; Arthur Zimek (CIKM, 2009)

Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data. - Hans-Peter Kriegel; Peer Kröger; Erich Schubert; Arthur Zimek (PAKDD, 2009)

ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series. - Elke Achtert; Thomas Bernecker; Hans-Peter Kriegel; Erich Schubert; Arthur Zimek (SSTD, 2009)

Visual Evaluation of Outlier Detection Models. - Elke Achtert; Hans-Peter Kriegel; Lisa Reichert; Erich Schubert; Remigius Wojdanowski; Arthur Zimek (DASFAA (2), 2010)

Subspace similarity search using the ideas of ranking and top-k retrieval. - Thomas Bernecker; Tobias Emrich; Franz Graf 001; Hans-Peter Kriegel; Peer Kröger; Matthias Renz; Erich Schubert; Arthur Zimek (ICDE Workshops, 2010)

Subspace Similarity Search: Efficient k-NN Queries in Arbitrary Subspaces. - Thomas Bernecker; Tobias Emrich; Franz Graf 001; Hans-Peter Kriegel; Peer Kröger; Matthias Renz; Erich Schubert; Arthur Zimek (SSDBM, 2010)

Can Shared-Neighbor Distances Defeat the Curse of Dimensionality? - Michael E. Houle; Hans-Peter Kriegel; Peer Kröger; Erich Schubert; Arthur Zimek (SSDBM, 2010)

Evaluation of Multiple Clustering Solutions. - Hans-Peter Kriegel; Erich Schubert; Arthur Zimek (MultiClust@ECML/PKDD, 2011)

Interpreting and Unifying Outlier Scores. - Hans-Peter Kriegel; Peer Kröger; Erich Schubert; Arthur Zimek (SDM, 2011)

Spatial Outlier Detection: Data, Algorithms, Visualizations. - Elke Achtert; Ahmed Hettab; Hans-Peter Kriegel; Erich Schubert; Arthur Zimek (SSTD, 2011)

Quality of Similarity Rankings in Time Series. - Thomas Bernecker; Michael E. Houle; Hans-Peter Kriegel; Peer Kröger; Matthias Renz; Erich Schubert; Arthur Zimek (SSTD, 2011)

Evaluation of Clusterings - Metrics and Visual Support. - Elke Achtert; Sascha Goldhofer; Hans-Peter Kriegel; Erich Schubert; Arthur Zimek (ICDE, 2012)

Outlier Detection in Arbitrarily Oriented Subspaces. - Hans-Peter Kriegel; Peer Kröger; Erich Schubert; Arthur Zimek (ICDM, 2012)

On Evaluation of Outlier Rankings and Outlier Scores. - Erich Schubert; Remigius Wojdanowski; Arthur Zimek; Hans-Peter Kriegel (SDM, 2012)

A survey on unsupervised outlier detection in high-dimensional numerical data. - Arthur Zimek; Erich Schubert; Hans-Peter Kriegel (Stat. Anal. Data Min., 2012)

Interactive data mining with 3D-parallel-coordinate-trees. - Elke Achtert; Hans-Peter Kriegel; Erich Schubert; Arthur Zimek (SIGMOD Conference, 2013)

Geodetic Distance Queries on R-Trees for Indexing Geographic Data. - Erich Schubert; Arthur Zimek; Hans-Peter Kriegel (SSTD, 2013)

Generalized and efficient outlier detection for spatial, temporal, and high-dimensional data mining. - Erich Schubert (2013)

Discriminative features for identifying and interpreting outliers. - Xuan-Hong Dang; Ira Assent; Raymond T. Ng; Arthur Zimek; Erich Schubert (ICDE, 2014)

SigniTrend: scalable detection of emerging topics in textual streams by hashed significance thresholds. - Erich Schubert; Michael Weiler; Hans-Peter Kriegel (KDD, 2014)

Generalized Outlier Detection with Flexible Kernel Density Estimates. - Erich Schubert; Arthur Zimek; Hans-Peter Kriegel (SDM, 2014)

Local outlier detection reconsidered: a generalized view on locality with applications to spatial, video, and network outlier detection. - Erich Schubert; Arthur Zimek; Hans-Peter Kriegel (Data Min. Knowl. Discov., 2014)

Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles. - Erich Schubert; Arthur Zimek; Hans-Peter Kriegel (DASFAA (2), 2015)

Outlier Detection and Trend Detection: Two Sides of the Same Coin. - Erich Schubert; Michael Weiler; Arthur Zimek (ICDM Workshops, 2015)

A Framework for Clustering Uncertain Data. - Erich Schubert; Alexander Koos; Tobias Emrich; Andreas Züfle; Klaus Arthur Schmid; Arthur Zimek (Proc. VLDB Endow., 2015)

SPOTHOT: Scalable Detection of Geo-spatial Events in Large Textual Streams. - Erich Schubert; Michael Weiler; Hans-Peter Kriegel (SSDBM, 2016)

On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. - Guilherme Oliveira Campos; Arthur Zimek; Jörg Sander 001; Ricardo J. G. B. Campello; Barbora Micenková; Erich Schubert; Ira Assent; Michael E. Houle (Data Min. Knowl. Discov., 2016)

Good and Bad Neighborhood Approximations for Outlier Detection Ensembles. - Evelyn Kirner; Erich Schubert; Arthur Zimek (SISAP, 2017)

Intrinsic t-Stochastic Neighbor Embedding for Visualization and Outlier Detection - A Remedy Against the Curse of Dimensionality? - Erich Schubert; Michael Gertz 001 (SISAP, 2017)

Semantic Word Clouds with Background Corpus Normalization and t-distributed Stochastic Neighbor Embedding. - Erich Schubert; Andreas Spitz; Michael Weiler; Johanna Geiß; Michael Gertz 001 (CoRR, 2017)

The (black) art of runtime evaluation: Are we comparing algorithms or implementations? - Hans-Peter Kriegel; Erich Schubert; Arthur Zimek (Knowl. Inf. Syst., 2017)

Dimensional Testing for Reverse k-Nearest Neighbor Search. - Guillaume Casanova; Elias Englmeier; Michael E. Houle; Peer Kröger; Michael Nett; Erich Schubert; Arthur Zimek (Proc. VLDB Endow., 2017)

DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN. - Erich Schubert; Jörg Sander 001; Martin Ester; Hans-Peter Kriegel; Xiaowei Xu 001 (ACM Trans. Database Syst., 2017)

Exploring Significant Interactions in Live News. - Erich Schubert; Andreas Spitz; Michael Gertz 001 (NewsIR@ECIR, 2018)

Improving the Cluster Structure Extracted from OPTICS Plots. - Erich Schubert; Michael Gertz 001 (LWDA, 2018)

The Relationship of DBSCAN to Matrix Factorization and Spectral Clustering. - Erich Schubert; Sibylle Hess; Katharina Morik (LWDA, 2018)

On the Correlation Between Local Intrinsic Dimensionality and Outlierness. - Michael E. Houle; Erich Schubert; Arthur Zimek (SISAP, 2018)

Numerically stable parallel computation of (co-)variance. - Erich Schubert; Michael Gertz 001 (SSDBM, 2018)

Outlier Detection. - Arthur Zimek; Erich Schubert (Encyclopedia of Database Systems (2nd ed.), 2018)

1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2019). - Eirini Ntoutsi; Erich Schubert; Arthur Zimek; Albrecht Zimmermann (EDML@SDM, 2019)

Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms. - Erich Schubert; Peter J. Rousseeuw (SISAP, 2019)

ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg". - Erich Schubert; Arthur Zimek (CoRR, 2019)

Introduction to Special Issue of the 9th International Conference on Similarity Search and Applications (SISAP 2016). - Laurent Amsaleg; Michael E. Houle; Erich Schubert (Inf. Syst., 2019)

BETULA: Numerically Stable CF-Trees for BIRCH Clustering. - Andreas Lang 002; Erich Schubert (SISAP, 2020)

ABID: Angle Based Intrinsic Dimensionality. - Erik Thordsen; Erich Schubert (SISAP, 2020)

Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning. - Eirini Ntoutsi; Erich Schubert; Arthur Zimek; Albrecht Zimmermann (Big Data, 2020)

HACAM: Hierarchical Agglomerative Clustering Around Medoids - and its Limitations. - Erich Schubert (LWDA, 2021)

CANDLE: Classification And Noise Detection With Local Embedding Approximations. - Erik Thordsen; Erich Schubert (LWDA, 2021)

Metric Indexing for Graph Similarity Search. - Franka Bause; David B. Blumenthal; Erich Schubert; Nils M. Kriege (SISAP, 2021)

A Triangle Inequality for Cosine Similarity. - Erich Schubert (SISAP, 2021)

Accelerating Spherical k-Means. - Erich Schubert; Andreas Lang 002; Gloria Feher (SISAP, 2021)

MESS: Manifold Embedding Motivated Super Sampling. - Erik Thordsen; Erich Schubert (SISAP, 2021)

Fast and eager k-medoids clustering: O(k) runtime improvement of the PAM, CLARA, and CLARANS algorithms. - Erich Schubert; Peter J. Rousseeuw (Inf. Syst., 2021)

Sparse Partitioning Around Medoids. - Lars Lenssen; Erich Schubert (Mach. Learn. under Resour. Constraints Vol. 1 (1), 2022)

Data Aggregation for Hierarchical Clustering. - Erich Schubert; Andreas Lang 002 (Mach. Learn. under Resour. Constraints Vol. 1 (1), 2022)

Clustering by Direct Optimization of the Medoid Silhouette. - Lars Lenssen; Erich Schubert (SISAP, 2022)

Automatic Indexing for Similarity Search in ELKI. - Erich Schubert (SISAP, 2022)

On Projections to Linear Subspaces. - Erik Thordsen; Erich Schubert (SISAP, 2022)

LOSDD: Leave-Out Support Vector Data Description for Outlier Detection. - Daniel Boiar; Thomas Liebig; Erich Schubert (CoRR, 2022)

EmbAssi: embedding assignment costs for similarity search in large graph databases. - Franka Bause; Erich Schubert; Nils M. Kriege (Data Min. Knowl. Discov., 2022)

BETULA: Fast clustering of large data with improved BIRCH CF-Trees. - Andreas Lang 002; Erich Schubert (Inf. Syst., 2022)

ABID: Angle Based Intrinsic Dimensionality - Theory and analysis. - Erik Thordsen; Erich Schubert (Inf. Syst., 2022)

Fast k-medoids Clustering in Rust and Python. - Erich Schubert; Lars Lenssen (J. Open Source Softw., 2022)

Who Did What When? Discovering Complex Historical Interrelations in Immersive Virtual Reality. - Melanie Derksen; Julia Becker; Mohammad Fazleh Elahi; Angelika Maier; Marius Maile; Ingo Oliver Pätzold; Jonas Penningroth; Bettina Reglin; Markus Rothgänger; Philipp Cimiano; Erich Schubert; Silke Schwandt; et al. (ISMAR, 2023)

Fast k-Nearest-Neighbor-Consistent Clustering. - Lars Lenssen; Niklas Strahmann; Erich Schubert (LWDA, 2023)

Accelerating k-Means Clustering with Cover Trees. - Andreas Lang 002; Erich Schubert (SISAP, 2023)

An Alternating Optimization Scheme for Binary Sketches for Cosine Similarity Search. - Erik Thordsen; Erich Schubert (SISAP, 2023)

Data Aggregation for Hierarchical Clustering. - Erich Schubert; Andreas Lang 002 (CoRR, 2023)

Sparse Partitioning Around Medoids. - Lars Lenssen; Erich Schubert (CoRR, 2023)

Stop using the elbow criterion for k-means and how to choose the number of clusters instead. - Erich Schubert (SIGKDD Explor., 2023)

Advancing the PAM Algorithm to Semi-supervised k-Medoids Clustering. - Miriama Jánosová; Andreas Lang 002; Petra Budíková; Erich Schubert; Vlastislav Dohnal (SISAP, 2024)

Hierarchical Clustering Without Pairwise Distances by Incremental Similarity Search. - Erich Schubert (SISAP, 2024)

Grouping Sketches to Index High-Dimensional Data in a Resource-Limited Setting. - Erik Thordsen; Erich Schubert (SISAP, 2024)

Explicit Formulae to Interchangeably use Hyperplanes and Hyperballs using Inversive Geometry. - Erik Thordsen; Erich Schubert (CoRR, 2024)

Accelerating k-Means Clustering with Cover Trees. - Andreas Lang; Erich Schubert (CoRR, 2024)

Medoid Silhouette clustering with automatic cluster number selection. - Lars Lenssen; Erich Schubert (Inf. Syst., 2024)

An Alternating Optimization Scheme for Binary Sketches. - Erik Thordsen; Erich Schubert (Inf. Syst., 2025)

A comparative evaluation of clustering-based outlier detection. - Braulio Valentin Sanchez Vinces; Erich Schubert; Arthur Zimek; Robson L. F. Cordeiro (Data Min. Knowl. Discov., 2025)