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start [2018/02/02 11:00]
vincent
start [2018/06/20 08:57] (current)
guilherme
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-====== Geometry, imaGes, learninG and alGorithms ======+====== Geometry, imaGes, learninGand alGorithms ======
  
 The research group **Geometry, imaGes, learninG and alGorithms** (G4) is a member of the [[http://​limos.isima.fr/​spip.php?​article9|Decision Support Models and Algorithms (MAAD)]] group. We are all part of the [[http://​limos.isima.fr/​spip.php?​article7|LIMOS lab]], in the Cézeaux campus of [[http://​uca.fr|Université Clermont Auvergne]], near Clermont Ferrand, France. The research group **Geometry, imaGes, learninG and alGorithms** (G4) is a member of the [[http://​limos.isima.fr/​spip.php?​article9|Decision Support Models and Algorithms (MAAD)]] group. We are all part of the [[http://​limos.isima.fr/​spip.php?​article7|LIMOS lab]], in the Cézeaux campus of [[http://​uca.fr|Université Clermont Auvergne]], near Clermont Ferrand, France.
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 ====== Short summary ====== ====== Short summary ======
-The research topics of this group are centered on n-dimensional data modeling and analysis, both from a methodological ​and an applicative point of view. The staff has interdisciplinary skills, and the projects ​developed in the group cover a wide range of scientific topics, at the boundaries of Computer Science and Geometry, Data Mining ​and Machine Learning, ​or data structures ​and applications.+The research topics of this group are centered on n-dimensional data modeling and analysis, ​from both methodology ​and application points ​of view. The team'​s ​interdisciplinary skills ​result in projects ​that cover a wide range of scientific topics ​including ​Geometry, Data MiningMachine Learning, ​Data Structures, ​and their interactions for several fields of application.
  
-Our research ​field include+For a brief description of our main research ​areas, we mention
  
-  * **Machine ​Learning**: several ​ aspects ​are addressed, from the design of kernel methods to manifold learning and deep learning. Current research include modeling and simulation of spatio-temporal variations and dynamics using manifolds, understanding of the GANs approaches and their link to Optimal Transport, Siamese network for multimodal learning and autoencoders or solving multiclass SVM at the cost of a binary one, dealing with indefinite kernels or large datasets. +  * **Machine ​learning**: We address ​several ​ aspects ​of machine learning, from the design of kernel methods to manifold learning and deep learning. Current research include modeling and simulation of spatio-temporal variations and dynamics using manifolds, understanding of the GANs approaches and their link to Optimal Transport, Siamese network for multimodal learning and autoencoders or solving multiclass SVM at the cost of a binary one, and dealing with indefinite kernels or large datasets.
-  * **Clustering methods**, using fuzzy clustering algorithms, or  semi-supervised clustering, also referred to as constrained clustering. Such methods use background knowledge in order to improve the accuracy of the solution +
-  * **Digital Geometry**, strongly related with many other topics going from geometry of numbers to computational geometry, discrete geometry, combinatorics or inverse problems. For instance, we are especially interested nowadays in questions of separability from a lattice set and its complementary on the grid.   +
-  * **Computational geometry** and geometric approximation,​ where we either approximate distances (e.g., approximate nearest neighbor searching) or the size of the solution (e.g., maximum independent set of a unit disk graph). Current works include the search of dramatic improvements to the complexity of several approximation problems such as polytope membership, nearest neighbor searching, epsilon-kernel,​ and diameter of a point set, using a hierarchy of Macbeath regions +
-  * **Image and Video Processing**,​ addressed from both a methodological (definition of image analysis methods in nD) and applicative points of view (tracking of ballistics in thermal videos of volcanoes, design of computer assisted maps  for visually impaired people,…)+
  
 +  * **Clustering methods**: We study fuzzy clustering algorithms, or  semi-supervised clustering, also referred to as constrained clustering. Such methods use background knowledge in order to improve the accuracy of the solution.
  
-International collaborations include Hong Kong University ​of Science ​and Technology ​(Hong Kong)University ​of Bergen ​(Norway), UCLAFSU, OSU, Houston Rice and Maryland Universities (USA)  Murdoch University ​and CSIRO (Australia), UCL and the Royal Observatory ​of Belgium ​(Belgium) or UDESC (Brazil). Among all national partners are LITIS (Rouen), LMV (Clermont-Ferrand) ​and Creatis (Lyon) ​labs.+  * **Digital geometry**: The field is closely related to many other topics such as geometry ​of numbers, computational geometry, discrete geometry, ​and combinatorics. We are especially interested in questions of separability from a lattice set and its complement, as well as the recognition of digital polytopes. 
 + 
 +  * **Geometric approximation**:​ We resort to approximations to solve geometric problems that would be intractable otherwise. We can either approximate distances ​(e.g.approximate nearest neighbor searching) or the size of the solution ​(e.g., maximum independent set of a unit disk graph)
 + 
 +  * **Computational geometry**: We design algorithms and data structures for numerous geometric problems related to range searchinggeometric graphs, and several other topics. We analyze that asymptotic complexity of these algorithms and also prove lower bounds for the complexity of the problems. 
 + 
 +  * **Image ​and video processing**:​ We address both the methodological ​(definition of image analysis methods in n dimension) and the  ​application points ​of view (tracking of ballistics in thermal videos of volcanoes, design of computer assisted maps for visually impaired people, ...). 
 + 
 +National collaborations include: ​LITIS (Rouen), LMV (Clermont-Ferrand), INRIA Sophia-Antipolis, ​Creatis (Lyon), IMT (Toulouse), LIFL (Lille) and IGN (Paris). 
 + 
 +International collaborations include: 
 + 
 +  * Australia: Murdoch University and CSIRO 
 +  * Belgium: Université Catholique de Louvain and the Royal Observatory of Belgium 
 +  * Brazil: UDESC and UFRJ 
 +  * Hong Kong: Hong Kong University of Science and Technology 
 +  * Norway: University of Bergen 
 +  * USA: University of California Los Angeles, Florida State University, Ohio State University, Rice University, and University of Maryland
  
 ===== News ===== ===== News =====