GSI’17 « Geometric Science of Information » November 7th to 9th, Paris - France CALL FOR PAPERS

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GSI2017

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07/11/2017
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As for GSI’13 and GSI’15, the objective of this SEE Conference GSI’17, hosted in Paris, is to bring together pure/applied mathematicians and engineers, with common interest for Geometric tools and their applications for Information analysis.
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Dear sir,
 

Following the success of GSI’13 & GSI’15, the organizing committe is honored to anounce GSI  2017 to be hosted at Mines ParisTech from November 7th to 9th.

We will welcome mathematicians and engineers, with common interest for Geometric tools and their applications for Information analysis.

It emphasizes an active participation of young researchers to discuss emerging areas of collaborative research on “Geometric Science of Information and their Applications”.

Current and ongoing uses of Information Geometry Manifolds in applied mathematics are the following: Advanced Signal/Image/Video Processing, Complex Data Modeling and Analysis, Information Ranking and Retrieval, Coding, Cognitive Systems, Optimal Control, Statistics on Manifolds, Topology/Machine/Deep Learning, Artificial Intelligence, Speech/sound recognition, natural language treatment, Big Data Analytics, etc., which are substantially relevant for industry.

The Conference will be therefore held in areas of priority/focused themes and topics of mutual interest with the aim to:

Provide an overview on the most recent state-of-the-art Exchange mathematical information/knowledge/expertise in the area Identify research areas/applications for future collaboration Identify academic & industry labs expertise for further collaboration

GSI 2017 will be an interdisciplinary event and will unify skills from Geometry, Probability and Information Theory.

Proceedings are published in Springer's Lecture Note in Computer Science (LNCS) series.  

 
IMPORTANT DATES:
  • April 3rd 2017 : Deadline for 8 pages SPRINGER LNCS format
  • June 12th 2017 : Notification of acceptance
  • July 31st 2017: Final paper submission

Paper templates (Latex, Word) and Guideline on GSI’17 website at “Author Instructions” www.gsi2017.org

 

The following Special Sessions have been identified but will not be limited to:

  • Statistics on non-linear data
  • Shape Space
  • Optimal Transport & Applications I (Data Science and Economics)
  • Optimal Transport & Applications II (Signal and Image Processing)
  • Topology and statistical learning
  • Statistical Manifold & Hessian Information Geometry
  • Information Structure in Neuroscience
  • Geometric Robotics & Tracking
  • Geometric Mechanics & Robotics
  • Stochastic Geometric Mechanics & Lie Group Thermodynamics
  • Probability on Riemannian Manifolds
  • Divergence Geometry
  • Geometric Deep Learning
  • First and second-order Optimization on Statistical Manifolds
  • Non-parametric Information Geometry
  • Geometry of quantum states
  • Optimization on Manifold
  • Computational Information Geometry
  • Probability Density Estimation
  • Geometry of Tensor-Valued Data
  • Geometry and Inverse Problems
  • Geometry in Vision, Learning and Dynamical Systems
  • Lie Groups and Wavelets
  • Geometry of metric measure spaces
  • Geometry and Telecom
  • Geodesic Methods with Constraints
  • Applications of Distance Geometry

3 keynote speakers’ talks will open each day (Prof. A. Trouvé, B. Tumpach & M. Girolami).  An Invited Honorary speaker (Prof. J.M. Bismut) will give a talk at the end of 1st day and a Guest Honorary speaker (Prof. D. Bennequin) will close the conference.

Invited Honorary Speaker

  • Jean-Michel Bismut (Paris-Saclay University) - The hypoelliptic Laplacian

Guest Honorary Speaker

  • Daniel Bennequin (Paris Diderot University) - Geometry and Vestibular Information

Keynote Speakers

  • Alain Trouvé (ENS Cachan) - Hamiltonian Modeling for Shape Evolution and Statistical Modeling of Shapes Variability
  • Barbara Tumpach (Lille University) - Riemannian Metrics on Shape Spaces of Curves and Surfaces
  • Mark Girolami (Imperial College London) - Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
 
GSI’17 Organizing committee
Groupes / audience: