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The last decade has seen an explosion of available data. To analyze the enormous amount of accrued data, classical algorithms are often not appropriate: the data may not be accessible in its entirety (but perhaps only in an aggregate form) and computations may need to be distributed or done in an online setting. The data often comes with an additional geometric flavor, either from applications or from mapping the data to feature spaces. The workshop will focus on three classes of algorithms for dealing with massive geometric data, namely, streaming, distributed, and sublinear algorithms. The aim of the workshop is to identify and explore new research directions at the interface of massive data models and computational geometry. This is an invitation-only workshop. |
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Invited talks by:
- Sariel Har-Peled (University of Illinois Urbana-Champaign, US)
- Eunjin Oh (POSTECH, KR)
- Sharath Raghvendra (North Carolina State University, US)
- Sandeep Silwal (University of Wisconsin-Madison, US)
- Christian Sohler (University of Cologne, DE)
Scientific organizers:
- Anne Driemel (University of Bonn)
- Morteza Monemizadeh (Eindhoven University of Technology)
- André Nusser (CNRS)
- Jeff M Phillips (University of Utah)
Participants:
- Ali Vakilian
- André Nusser
- Anne Driemel
- Annika Hennes
- Benedikt Kolbe
- Chris Schwiegelshohn
- Christian Sohler
- Dan Feldman
- Danny Mittal
- Di Yue
- Eunjin Oh
- Evangelos Kipouridis
- Frank Staals
- Ioannis Psarros
- Jacobus Conradi
- Jan Höckendorff
- Jeff Giliberti
- Jeff Phillips
- Jie Gao
- Johanna Hillebrand
- Jonas Sauer
- Karl Bringmann
- Krzysztof Onak
- Lotte Blank
- Marena Richter
- Mohammad Hajiaghayi
- Mónika Csikós
- Morteza Monemizadeh
- Niko Hastrich
- Nodari Sitchinava
- Peyman Afshani
- Sandeep Silwal
- Sariel Har-Peled
- Sebastian Angrick
- Sharath Raghvendra
- Shay Sapir
- Siu-Wing Cheng
- Tim Sinen
- Yanheng Wang