Christian Sohler

Artificial Intelligence · 2010–2018

A researcher in the Science corpus: 4 papers; trusts 10 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it; #8,729 of 35,345 by trust here, #10,798 by citations
• Computer Vision and Pattern Recognition — 20 citations into it
• Signal Processing — 20 citations into it; #6,579 of 7,572 by trust here, #3,784 by citations
• Computational Theory and Mathematics — 18 citations into it; #2,723 of 12,182 by trust here, #3,218 by citations
• Computer Graphics and Computer-Aided Design — 13 citations into it
• Computational Mechanics — 11 citations into it; #2,306 of 10,001 by trust here, #3,190 by citations
• Algorithms & Complexity — 7 citations into it
• Safety, Robustness & Interpretability — 7 citations into it

Whom Christian Sohler trusts overall

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

1. David Arthur
2. Sariel Har-Peled
3. Dan Feldman
4. Pankaj Kumar Agarwal
5. Sergei Vassilvitskii

Who trusts Christian Sohler overall

1. David P. Woodruff
2. Dan Feldman
3. Melanie Schmidt
4. Trevor Campbell
5. Mario Lucic

Papers from Christian Sohler's perspective

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

1. On coresets for k-means and k-median clustering
2. Least squares quantization in PCM
3. Approximating extent measures of points (JACM)
4. Certifying and Removing Disparate Impact
5. A local search approximation algorithm for k-means clustering (SCG '02)
6. Some methods for classification and analysis of multivariate observations
7. Equality of Opportunity in Supervised Learning
8. Algorithmic Decision Making and the Cost of Fairness
9. Distinctive Image Features from Scale-Invariant Keypoints
10. Approximate clustering via core-sets (Symposium on the Theory of Computing)

Their papers

• Fair Coresets and Streaming Algorithms for Fair k-Means Clustering (2018) — 42 citations
• Turning big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering (2013) — 591 citations
• BICO: BIRCH Meets Coresets for k-Means Clustering (2013) — 79 citations
• StreamKM++: A clustering algorithm for data streams (2010) — 371 citations