Erich Schubert

Artificial Intelligence · 2009–2018

A researcher in the Science corpus: 7 papers; trusts 35 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 76 citations into it; #6,480 of 35,345 by trust here, #8,810 by citations
• Signal Processing — 43 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Biomedical Engineering — 14 citations into it; #4,308 of 10,734 by trust here, #8,749 by citations
• Computer Networks and Communications — 14 citations into it
• Statistics and Probability — 14 citations into it; #2,971 of 12,932 by trust here, #1,989 by citations
• Information Systems — 12 citations into it
• Algorithms & Complexity — 9 citations into it

Whom Erich Schubert trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Hans-Peter Kriegel
2. David Arthur
3. Raymond T. Ng
4. Fabrizio Angiulli
5. Jiawei Han
6. Hae-Sang Park
7. Arthur Zimek
8. Peer Kröger
9. Wen Jin
10. Martin Ester

Who trusts Erich Schubert overall

1. Arthur Zimek
2. Ricardo José Gabrielli Barreto Campello
3. Charu C. Aggarwal
4. Guansong Pang
5. Hongzhi Wang
6. Hans-Peter Kriegel
7. Jörg Sander
8. Zhen Wang
9. Chunhua Shen
10. Davoud Moulavi

Papers from Erich Schubert's perspective

Ordered by how strongly the researchers Erich Schubert trusts endorse each paper. Same corpus, a different order for every researcher.

1. LOF: identifying density-based local outliers
2. Efficient algorithms for mining outliers from large data sets (ACM SIGMOD Conference)
3. When Is ''Nearest Neighbor'' Meaningful?
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Multidimensional binary search trees used for associative searching
6. ImageNet classification with deep convolutional neural networks
7. The X-tree : An Index Structure for High-Dimensional Data (Very Large Data Bases Conference)
8. The WEKA data mining software: an update
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Angle-based outlier detection in high-dimensional data (Knowledge Discovery and Data Mining)

Their papers

• LoOP: local outlier probabilities (2009) — 576 citations
• A survey on unsupervised outlier detection in high‐dimensional numerical data (2012) — 858 citations
• Interpreting and Unifying Outlier Scores (2011) — 300 citations
• Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data (2009) — 320 citations
• Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms (2018) — 309 citations
• DBSCAN Revisited, Revisited (2017) — 1,779 citations
• Can Shared-Neighbor Distances Defeat the Curse of Dimensionality? (2010) — 305 citations