Section: Bilateral Contracts and Grants with Industry

European Initiatives

FP7 Projects

  • Title: Computational Geometric Learning


  • Defi: FET Open

  • Instrument: Specific Targeted Research Project (STREP)

  • Duration: November 2010 - October 2013

  • Coordinator: Friedrich-Schiller-Universität Jena (Germany)

  • Others partners: National and Kapodistrian University of Athens (Greece), Technische Universität Dortmund (Germany), Tel Aviv University (Israel), Eidgenössische Technische Hochschule Zürich (Switzerland), Rijksuniversiteit Groningen (Netherlands), Freie Universität Berlin (Germany)

  • See also: http://cgl.uni-jena.de/

  • Abstract: The Computational Geometric Learning project aims at extending the success story of geometric algorithms with guarantees to high-dimensions. This is not a straightforward task. For many problems, no efficient algorithms exist that compute the exact solution in high dimensions. This behavior is commonly called the curse of dimensionality. We try to address the curse of dimensionality by focusing on inherent structure in the data like sparsity or low intrinsic dimension, and by resorting to fast approximation algorithms.

  • Title: Robust Geometry Processing

  • Type: IDEAS

  • Instrument: ERC Starting Grant (Starting)

  • Duration: January 2011 - December 2015

  • Coordinator: Pierre Alliez, Inria Sophia Antipolis - mediterranee (France)

  • See also: http://www-sop.inria.fr/geometrica/collaborations/iron/

  • Abstract: The purpose of this project is to bring forth the full scientific and technological potential of Digital Geometry Processing by consolidating its most foundational aspects. Our methodology will draw from and bridge the two main communities (computer graphics and computational geometry) involved in discrete geometry to derive algorithmic and theoretical contributions that provide both robustness to noisy, unprocessed inputs, and strong guarantees on the outputs. The intended impact is to make the digital geometry pipeline as generic and ironclad as its Digital Signal Processing counterpart.