2007 - ACM Senior Member
His primary scientific interests are in Artificial intelligence, Bregman divergence, Combinatorics, Exponential family and Kullback–Leibler divergence. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Computer vision and Pattern recognition. Frank Nielsen works mostly in the field of Bregman divergence, limiting it down to topics relating to Weighted Voronoi diagram and, in certain cases, Bowyer–Watson algorithm and Computational geometry, as a part of the same area of interest.
The Combinatorics study combines topics in areas such as Centroid, Divergence, Applied mathematics, Euclidean geometry and Geodesic. His research integrates issues of Entropy, Class, Affine connection and Probability distribution in his study of Exponential family. His studies deal with areas such as Algorithm, Triangle inequality and Mathematical analysis, Piecewise as well as Kullback–Leibler divergence.
Frank Nielsen focuses on Artificial intelligence, Cluster analysis, Combinatorics, Exponential family and Computer vision. His study looks at the relationship between Artificial intelligence and topics such as Pattern recognition, which overlap with Classification rule. His Cluster analysis research is multidisciplinary, incorporating perspectives in Algorithm, Data mining and Series.
His Combinatorics research incorporates elements of Set, Voronoi diagram, Bregman divergence, Computational geometry and Geodesic. The various areas that Frank Nielsen examines in his Bregman divergence study include Kullback–Leibler divergence, Mathematical analysis and Convex function. His work deals with themes such as Mixture model, Probability distribution and Pure mathematics, which intersect with Exponential family.
His main research concerns Divergence, Cluster analysis, Information geometry, Applied mathematics and Combinatorics. His Divergence research includes themes of Kullback–Leibler divergence, Bregman divergence, Parametric family, Limit and Cauchy distribution. His Bregman divergence research focuses on Parametric statistics and how it connects with Algorithm.
His Cluster analysis study combines topics in areas such as Data mining, Time complexity, Dynamic programming, Multi-objective optimization and Optimization problem. Frank Nielsen has included themes like Space and Bhattacharyya distance in his Combinatorics study. Frank Nielsen focuses mostly in the field of Invariant, narrowing it down to matters related to Artificial intelligence and, in some cases, Geodesic.
His primary areas of study are Divergence, Information geometry, Pure mathematics, Exponential family and Bregman divergence. His Divergence study which covers Cauchy distribution that intersects with Parametric family, Jensen–Shannon divergence, Hyperbolic geometry, Voronoi diagram and Delaunay triangulation. His Bregman divergence study integrates concerns from other disciplines, such as Kullback–Leibler divergence and Convex function.
His Kullback–Leibler divergence study combines topics from a wide range of disciplines, such as Mixture model, Mathematical analysis and Applied mathematics. The subject of his Curse of dimensionality research is within the realm of Artificial intelligence. His Artificial intelligence study incorporates themes from Unary operation and Natural language processing.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Statistical region merging
R. Nock;F. Nielsen.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)
On weighting clustering
R. Nock;F. Nielsen.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)
Image processing apparatus, image processing method, and computer program
DeepBach: a steerable model for bach chorales generation
Gaëtan Hadjeres;François Pachet;Frank Nielsen.
international conference on machine learning (2017)
K-nearest neighbor search: Fast GPU-based implementations and application to high-dimensional feature matching
Vincent Garcia;Eric Debreuve;Frank Nielsen;Michel Barlaud.
international conference on image processing (2010)
Sided and Symmetrized Bregman Centroids
F. Nielsen;R. Nock.
IEEE Transactions on Information Theory (2009)
Statistical exponential families: A digest with flash cards
Frank Nielsen;Vincent Garcia.
arXiv: Learning (2009)
Hydronephrosis during pregnancy: a literature survey.
Per Emil Rasmussen;Frank Rohde Nielsen.
European Journal of Obstetrics & Gynecology and Reproductive Biology (1988)
Non-flat image processing apparatus, image processing method, recording medium, and computer program
Matrix Information Geometry
Frank Nielsen;Rajendra Bhatia.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: