This Special Issue "Differential Geometrical Theor y of Statistics" collates selected invited and contributed talks presented during the conference GSI'15 on "Geometric Science of Information" which was held at the Ecole Polytechnique, Paris-Saclay Campus, France, in October 2015 (Conference web site: http://www.see.asso.fr/gsi2015).
www.mdpi.com/journal/entropy/special_issues/entropy-statistics
ISBN 978-3-03842-424-6 (print) • ISBN 978-3-03842-425-3 (electronic)
 

A propos

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.
It emphasizes an active participation of young researchers to discuss emerging areas of collaborative research on “Information Geometry Manifolds and Their Advanced 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, Machine & Deep Learning, Artificial Intelligence, Speech/sound recognition, natural language treatment, Big Data Analytics, etc., which are also 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
This conference will be an interdisciplinary event and will unify skills from Geometry, Probability and Information Theory. The conference proceedings are published in Springer's Lecture Note in Computer Science (LNCS) series.
Provisional Topics of Special Sessions:
  • 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
  • Monotone Embedding in 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

Faces in the banner, in order: Euclide, Thales, Clairaut, Legendre, Poncelet, Darboux, Poincaré, Cartan, Fréchet, Libermann, Leray, Koszul, Ferrand, Souriau, Balian, Berger, Choquet-Bruhat, Gromov
Music is from Pascal Dusapin (born 29 May 1955) is a contemporary French composer born in Nancy, France. His music is marked by its microtonality, tension, and energy. A pupil of Iannis Xenakis and Franco Donatoniand an admirer of Varèse, Dusapin studied at the University of Paris I and Paris VIII during the 1970s. His music is full of "romantic constraint", and he rejects the use of electronics, percussion other than timpani, and, up until the late 1990s, piano. His melodies have a vocal quality, even in purely instrumental works. Dusapin has composed solo, chamber, orchestral, vocal, and choral works, as well as several operas, and has been honored with numerous prizes and awards.
 

Informations

    The "calculation of probabilities" began four years after the death of René Descartes [4][5][6][7][8][9][10], in 1654, in a correspondence between Blaise Pascal and Pierre Fermat [1][11][13][14][16][21][22][32]. They exchanged letters on elementary problems of gambling, in this case a problem of dice and a problem of "parties".  Pascal and Fermat were particularly interested by this problem and succeeded in "Party rule" by two different methods.  One understands the legitimate pride of Pascal in his address of the same year at the Académie Parisienne created by Mersenne, to which he presented, among "the ripe fruit of our Geometry" (“les fruits mûrs de notre Géométrie” in french) an entirely new treaty, of an absolutely unexplored matter, the distribution of chance in the games. In the same way, Pascal in his introduction to “Les Pensées” wrote that "under the influence of Méré, given to the game, he throws the bases of the calculation of probabilities and composes the Treatise of the Arithmetical Triangle. If Pascal appears at first sight as the initiator of the calculation of probabilities, watching a little closer, its role in the emergence of this theory is more complex. However, there is no trace of the word probabilities in Pascal's work. To designate what might resemble what we now call calculation of probabilities, one doesn’t even find the word in such a context. The only occurrences of probability are found in “Les Provinciales” where he referred to the doctrine of the Jesuits, or in “Les Pensées”. We do not find in Pascal's writings, the words of “Doctrine des chances”, or “Calcul des chances”, but only “Géométrie du hasard” (geometry of chance). In 1654, Blaise Pascal submitted a short paper to "Celeberrimae matheseos Academiae Parisiensi" (ancestor of the French Royal Academy of Sciences founded in 1666), with the title "Aleae Geometria” (Geometry of Chance) or “De compositione aleae in ludis ipsi subjectis", that was the seminal paper founding Probability as a new discipline in Science. In this paper, Pascal said “… et sic matheseos demonstrationes cum aleae incertitudine jugendo, et quae contraria videntur conciliando, ab utraque nominationem suam accipiens, stupendum hunc titulum jure sibi arrogat: Aleae Geometria” that we can translate as “By the union thus realized between the demonstrations of mathematics and the uncertainty of chance, and by the conciliation of apparent contradictions, it can derive its name from both sides and arrogate to itself this astonishing title: Geometry of Chance” (« … par l’union ainsi réalisée entre les démonstrations des mathématiques et l’incertitude du hasard, et par la conciliation entre les contraires apparents, elle peut tirer son nom de part et d’autre et s’arroger à bon droit ce titre étonnant: Géométrie du Hasard ». We can observe that Blaise Pascal attached a geometrical sense to probabilities in this seminal paper.  As Jacques Bernoulli, we can also give references to another Blaise Pascal document entitled “Art de penser” (the “Logique” of Port-Royal), published the year of his death (1662), with last chapters containing elements on the calculus of probabilities applied to history, to medicine, to miracles, to literary criticism, to events of life, etc.
   In “De l'esprit géométrique », the use of reason for knowledge is thought on a geometric model. In geometry, the first principles are given by the natural lights common to all men, and there is no need to define them. Other principles are clearly defined by definitions of names such that it is always possible to mentally substitute the definition for the defined [23][24][25]. These definitions of names are completely free, the only condition to be respected is univocity and invariability.  Judging his solution as one of his most important contributions to science, Pascal envisioned the drafting of a small treatise entitled “Géométrie du Hasard” (Geometry of Chance). He will never write it. Inspired by this, Christian Huygens wrote the first treatise on the calculation of chances, the “De ratiociniis in ludo aleae” ("On calculation in games of chance", 1657). We can conclude this preamble by observing that seminal work of Blaise Pascal on Probability was inspired by Geometry. The objective of GSI conference is to come back to this initial idea that we can geometrize statistics in a rigorous way.
   We can also make reference to Blaise Pascal for this GSI conference on computing geometrical statistics, because he was the inventor of computer with his “Pascaline” machine. The introduction of Pascaline marks the beginning of the development of mechanical calculus in Europe. This development, which will pass from the calculating machines to the electrical and electronic calculators of the following centuries, will culminate with the invention of the microprocessor. But it was also Charles Babbage who conceived his analytical machine from 1834 to 1837, a programmable calculating machine which was the ancestor of the computers of the 1940s, combining the inventions of Blaise Pascal and Jacquard’s machine, with instructions written on perforated cards, one of the descendants of the Pascaline, the first machine which supplied the intelligence of man.
 
References:
[1] ABOUT, P.J., BOY, M., «La correspondance de Blaise Pascal et de Pierre de Fermat», Cahiers de Fontenay, n° 32, p. 59-73.
[2] BARBARESCO, F., “Les densités de probabilité « distinguées » et l’équation d’Alexis Clairaut:                                                regards croisés de Maurice Fréchet et de Jean-Louis Koszul », Colloque GRETSI’17, Juan-Les-Pins-September 2017
[3] BARBARESCO, F. & DJAFARI, A., ”Information, Entropy and Their Geometric Structures”, MDPI Entropy, September 2015; http://www.mdpi.com/books/pdfview/book/127
[4] BAYES, Th., «An essay towards solving a problem in the doctrine of chance», Philosophical Transactions of the Royal Society of London, 53 (1763), trad. J.-P. Cléro, Cahiers d'histoire et de philosophie des sciences, n° 18, 1988.
[5] BERNOULLI, J., Ars conjectandi (1713), die Werke von Jakob Bernoulli, 3 vols., Basel, 1969-1975.
[6] BYRNE, E., Probability and Opinion: A Study in the Medieval Pre-suppositions of Post-Medieval Theories of probability, La Haye, Martinus Nijhoff, 1968.
[7] CARDANO, De ludo aleae (ca. 1520), Opera Omnia, 10 vols., Stuttgart, 1966.
[8] CARDANO, The Book on Games of Chance, trad. S. H. Gould, New York, 1961.
[9] DASTON, L., Probability in the Enlightenment, Princeton, 1988.
[10] DAVID, F. N., Games, Gods and Gambling, A History of Probability and Statistical Ideas, London, Charles Griffin & Co, 1962.
[11] DAVIDSON, H. M., Pascal and the Arts of the Mind, Cambridge, Cambridge University Press, 1993.
[12] DE MOIVRE, A., The Doctrine of Chances, 3rd edition, London, 1756.
[13] EDWARDS, A. W. F., «Pascal and the Problem of Points», International Statistical Review, t. 51, 1983, p. 259-266.
[14] EDWARDS, A. W. F., «Pascal's Problem: The Gambler's Ruin», International Statistical Review, t. 50, 1982, p. 73-79.
[15] FRECHET M., Sur l’extension de certaines évaluations statistiques au cas de petits échantillons. Revue de l’Institut International de Statistique 1943, vol. 11, n° 3/4, pp. 182–205.
[16] GODFROY-GÉNIN A.S., Pascal la Géométrie du Hasard, Math. & Sci. hum., (38e année, n° 150, 2000, p. 7-39
[17] HACKING, I., The Emergence of Probability, Cambridge, 1975.
[18] KENDALL, M. G., PEARSON, E. S., (eds.)., Studies in the History of Statistics and Probability, 2 vols., London, 1970-1977.
[19] LEIBNIZ, G. W., «Nouveaux essais sur l'entendement humain», Sämtliche Schriften und Briefe, Berlin, 1962-1980, réed. Garnier-Flammarion, 1966.
[20] LEIBNIZ, G. W., Opuscules et fragments inédits, Couturat, ed., Paris, 1961.
[21] ORE, O., Cardano, the gambling scholar, Princeton, 1953.
[22] «Pascal et les probabilités», Cahiers Pédagogiques de philosophie et d'histoire des mathématiques, fascicule 4, IREM et CRDP de Rouen, 1993.
[23] PASCAL, B., Les Provinciales, Paris, Le Guern éd., 1987.
[24] PASCAL, B., Oeuvres complètes, J. Mesnard éd., 4 volumes publiés, 1964-1970.
[25] PASCAL, B., Pensées de Pascal, Paris, Ph. Sellier éd., 1991.
[26] PEARSON, K., The History of Statistics in the 17th and 18th Centuries, London, E.S. Pearson, ed., 1978.
[27] SCHNEIDER, I., «Why do we find the origin of a calculus of probabilities in the seventeenth century ?», Pisa Conference Proceedings, vol. 2, Dordrecht and Boston, J.Hintikka, D. Gruender, E. Agazzi eds., 1980.
[28] SCHNEIDER, I., Die Entwicklung des Wahrscheinlichkeitsbegriff in des Mathematik von Pascal bis Laplace, Munich, 1972.
[29] SHEYNIN, O., «On the early history of the law of large numbers», Studies in the History of Statistics and Probability, vol. 1, Paerson and Kendall eds., 1970.
[30] SHEYNIN, O., «On the prehistory of the theory of probability», Archives for History of Exact Sciences 12, 1974.
[31] STIGLER, S., The History of Statistics: The measurement of Uncertainety Before 1900, Cambridge (Mass.), The Belknap Press of Harvard University Press, 1986.

[32] TODHUNTER, I., A History of Mathematical Theory of Probability from the Time of Pascal to that of Laplace, Cambridge et Londres, Macmillan, 1865.

Comités

Comité d'organisation

Scientific committee

Sponsors et organisateurs

Nouvelles

This Special Issue "Differential Geometrical Theor y of Statistics" collates selected invited and contributed talks presented during the conference GSI'15 on "Geometric Science of Information" which was held at the Ecole Polytechnique, Paris-Saclay Campus, France, in October 2015 (Conference web site: http://www.see.asso.fr/gsi2015).
www.mdpi.com/journal/entropy/special_issues/entropy-statistics
ISBN 978-3-03842-424-6 (print) • ISBN 978-3-03842-425-3 (electronic)
 
Dear colleagues,
 
We are currently collecting papers for a special issue of Optimization Letters (OPTL, Springer) that is dedicated to the memory of Michel Deza (https://en.wikipedia.org/wiki/Michel_Deza). The title of the issue is "Applications of Distance Geometry".
Michel suddenly passed away on last November 2016. He is author of the Encyclopedia of Distances, that almost reached the threshold of 1000 citations, and which makes him an eminent member of the distance geometry community.
 
OPTL generally collects short contributions (about 10 pages long).
Submissions should be performed via the editorial system at the address:
 
by selecting the article type si:DGD16. The submission deadline is June 2nd, 2017.
 
All the best,
 
Antonio Mucherino
Carlile Lavor
OPTL guest co-editors
Call for Paper GSI17
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
The journal Information Geometry has taken up the challenge of how to think about and to look at mathematical science.
In principle, Information Geometry can connect various branches of mathematical sciences to allow for uncertainty from geometric thinking. There is still great potential for exploring new paradigms to break through conventional notions. The journal will publish papers on such research along with those on application of information geometry, broadly construed, emphasizing both theoretical and computational aspects. 
Topics of interests will include, but not be limited to, the Fisher–Rao metric, dual connections, divergence functions, entropy/cross-entropy, Hessian geometry, exponential/mixture geodesics and projections, Q-statistics, quantum statistical inference and computation, computational information geometry, algebraic statistics, optimal transportation problems, deep neural networks, and related topics. 
The authors and audience of the journal will be interdisciplinary, coming from mathematics, statistics, machine learning, statistical and quantum physics, information theory, control theory, neural computation, complex networks, cognitive science, and allied disciplines.
Annonce lancement Journal SPRINGER "Information Geometry"
We just learned that Michel Deza, died on 23 nov 2016. Michel was not only a excellent mathematician but also an humanist.
Michel did considerable contributions to mathematics, one of the most famous being the Encyclopedia of Distances (Springer) which he wrote with his wife Elena.

Michel was in the board of the GSI conferences since 2013.

Situation

Mines ParisTech, Paris (France)

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« Se défier du ton d’assurance qu’il est si facile de prendre et si dangereux d’écouter »
Charles Coquebert, Journal des mines n°1, Vendémiaire An III (septembre 1794)
 
60 Boulevard Saint-Michel, 75006 Paris