Chris Schwiegelshohn   Tenure Track Assistant Professor MADALGO (Center for Massive Data Algorithmics)  Deparment of Computer Science Aarhus University

Velkommen, Benvenuto, Welcome!

In case you are confusing me with some other Chris Schwiegelshohn out there, I am the one working as a faculty member of the computer science department of Aarhus University.

I was previously working at Sapienza University. If you are a student with questions about one of my past courses, please contact me under <cschwiegelshohn"at"gmail.com>.

If you are not a former student of mine but want to contact me anyway, well it's the same email.

I work mostly on algorithm design. In particular, I like online, streaming, approximation and learning algorithms.

Publications you cannot find below you may be able to find at dblp or google scholar.

Publications:

• Polynomial Time Approximation Schemes for All 1-Center Problems on Metric Rational Set Similarities, Algorithmica 2021. With Marc Bury, Michele Genitili, and Mara Sorella. pdf

• A New Coreset Framework for Clustering, STOC 2021 (to appear). With Vincent Cohen-Addad and David Saulpic.

• Similarity Search for Dynamic Data Streams, IEEE Trans. Knowl. Data Eng. 2020. With Marc Bury and Mara Sorella. pdf

• Spectral Relaxations and Fair Densest Subgraph, CIKM 2020. With Aris Anagnostopoulos, Luca Becchetti, Adriano Fazzone, and Cristina Menghini. pdf

• Commitment and Slack for Online Load Maximization , SPAA 2020. With Samin Jamalabadi and Uwe Schwiegelshohn. pdf

• Structural Results on Matching Estimation with Applications to Streaming, Algorithmica 2019. With Marc Bury, Elena Grigorescu, Andrew McGregor, Morteza Monemizadeh, Sofya Vorotnikova, and Samson Zhou. pdf

• Fully Dynamic Consistent Facility Location, NeurIPS 2019. With Vincent Cohen-Addad, Niklas Hjuler, Nikos Parotsidis, and David Saulpic. pdf

• Fair Coresets and Streaming Algorithms for Fair k-Means, WAOA 2019. With Melanie Schmidt and Christian Sohler. pdf

• Oblivious Dimension Reduction for k-Means -- Beyond Subspaces and the Johnson-Lindenstrauss Lemma, STOC 2019. With Luca Becchetti, Marc Bury, Vincent Cohen-Addad, and Fabrizio Grandoni. pdf
  I encourage anyone interested in this work to read the paper by Makarychev, Makarychev, and Razenshteyn. Independently from us, they obtained essentially optimal bounds for the same problem.

• (1 + ε)-Approximate Incremental Matching in Constant Deterministic Amortized Time, SODA 2019. With Fabrizio Grandoni, Stefano Leonardi, Piotr Sankowski, and Shay Solomon. pdf

• Coresets-Methods and History: A Theoreticians Design Pattern for Approximation and Streaming Algorithms, Künstliche Intelligenz 2018. With Alexander Munteanu. pdf

• On Coresets for Logistic Regression, NeurIPS 2018. With Alexander Munteanu, Christian Sohler, and David Woodruff. pdf

• Sketch 'Em All: Fast Approximate Similarity Search in Dynamic Data Streams, WSDM 2018. With Marc Bury and Mara Sorella.

• On the Local Structure of Stable Clustering Instances, FOCS 2017. With Vincent Cohen-Addad. pdf

• On Finding the Jaccard Center, ICALP 2017. With Marc Bury. pdf

• The Power of Migration for Online Slack Scheduling, ESA 2016. With Uwe Schwiegelshohn. pdf

• Diameter and k-Center in Sliding Windows, ICALP 2016. With Vincent Cohen-Addad and Christian Sohler. pdf

• Sublinear Estimation of Weighted Matchings in Dynamic Data Streams, ESA 2015. With Marc Bury.

• BICO: BIRCH Meets Coresets for k-Means Clustering, ESA 2013. With Hendrik Fichtenberger, Marc Gillé (now Bury), Melanie Schmidt, and Christian Sohler. pdf

• Solving the Minimum String Cover Problem, ALENEX 2012. With Stefan Canzar, Tobias Marshall, and Sven Rahmann. pdf