Conferences and Meetings on Probability and Statistics, Game Theory

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Neural Networks and Artificial Intelligence, Machine Learning,    Pattern Recognition and Image Processing, Machine Vision

Kyoto University/University of Tsukuba

Astrostatistics is developing fast as astronomy is confronted to huge volumes of data. This constitutes undoubtly a new era through a move from object- to data-driven astrophysics. We can distinguish two types of challenges: the first one is related to the exploration of the data space and the second one is the physical interpretation of the results of this exploration. Astrostatistics cannot be reduced to the technical issues brought by methods and algorithms required to analyse the data. Despite these tools are not part of the cursus of astronomers, things are changing rapidly through schools, training sessions, collaborations with experts (statisticians) as well as developments of specific tools adapted to astronomical data. The use of new techniques pervades the astronomical literature. To convince more and more astronomers to switch to this new approach to do science, it is important to demonstrate the relevance of astrostatistics results.

Phone: [+39-049-8278233];     Email: mauro.donofrio@unipd.it

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Uncertainty quantification (UQ) is essential for producing informative computational predictions in a wide range of sciences and engineering. The field relies on a broad range of mathematical and statistical foundations, with associated algorithmic and computational developments. This conference will bring together mathematicians, statisticians, scientists, and engineers with an interest in the development and implementation of uncertainty quantification methods. Major conference themes will include the mathematical and statistical foundations of UQ, applications of UQ in the physical sciences and biosciences, and connections between UQ and machine learning. The goal of the meeting is to provide a forum to share ideas and enhance communication among this diverse group of technical experts, thereby contributing to future advances in the field.

Bernoulli Center (CIB)

Functional data such as space curves, images, and surfaces are seldom sensed directly; curves are often noisily and discretely sampled, images are subject to blurring and deformation, and surfaces are often obtained via indirect linear measurements. Understanding the generation of the observations then requires modelling the act of acquisition, and solving an inverse problem in order to arrive at statistical inferences. This leads to a host of new research questions, from identifiability to trade-offs between statistical optimality and computational feasibility, which also make contact with signal processing and numerical analysis.

Part of the Semester : Functional Data Analysis

Acadia University

Artificial intelligence (AI) is mainly data-driven. It uses statistical methods through human-machine relationships during generation of data, production of algorithm, and prediction of results. The International Workshop on Statistical Methods and Artificial Intelligence will be an annual meeting of researchers in artificial intelligence, statistical methods, machine learning, and related areas.

Artificial Intelligence, Statistical methods, Data Analysis and Data mining, Computational Statistic, Supervised and unsupervised learning, Statistical methodology, Bioinformatics, Medical statistics, Deep Learning, Data Collection and Applications, Data Science and Blockchain Technology, Data Science and Artificial Intelligence, Data Science and Blockchain Technology, Mathematical Statistics, Sampling Techniques and Applications, Statistical Software R, SAS, Python

University of Bejaia

The advancement in computing and storage capabilities of modern computational clusters fosters use of novel statistical techniques in machine learning and deep networks. Such data-driven techniques allow one to learn model features and characteristics that are difficult for mathematical methods alone to reveal. Many computational methods achieve model and complexity discovery using methods that lie at the nexus of mathematical, statistical, and computational disciplines. Statistical methods often employ "big data" approaches that glean predictive capability from diverse and enormous databases of information. Emerging methods in machine learning and deep networks can provide impressive results. This workshop gathers researchers at the frontier of large-scale statistical computation, data science, tensor decompositions and approximations, and data-driven model learning, to focus on modern challenges that use data to reduce complexity of models.

The Fields Institute

Institute for Mathematical Sciences/National University of Singapore

Random matrix theory is an active branch of probability. It has important applications in statistics, wireless communication and physics, and is closely related to other areas of mathematics, like representation theory, integrable systems, combinatorics, and complex analysis.

Complex Networks,    Complex Systems, Chaos and Self-Organisation

Bernoulli Center (CIB)

Topological and discrete data such as trees and networks constitute strongly non-Euclidean structures, often beyond the reach of traditional statistical tools. Their analysis is often challenged by computational tractability, as natural constraints such as permutation invariance are computationally hard to implement. Still, such data can be often transposed into more familiar contexts, whether by transformation, asymptotic arguments, or replicated observations. This workshop will explore both modelling and processing of discrete structures, also drawing in areas such as signal processing on graphs and nonparametrics.

Part of the Semester : Functional Data Analysis

ISAST - non-profit organization

The Stochastic Modeling Techniques and Data Analysis International Conference (SMTDA) main objective is to welcome papers, both theoretical or practical, presenting new techniques and methodologies in the broad area of stochastic modeling and data analysis. An objective is to use the methods proposed for solving real life problems by analyzing the relevant data. Also, the use of recent advances in different fields will be promoted such as for example, new optimization and statistical methods, data warehouse, data mining and knowledge systems, computing-aided decision supports and neural computing. Particular attention will be given to interesting applications in engineering, productions and services (maintenance, reliability, planning and control, quality control, finance, insurance, management and administration, inventory and logistics, marketing, environment, human resources, biotechnology, medicine, ...).

SMTDA2020 Secretariat;     Email: secretariat@smtda.net

Poisson, Markov, semi-Markov processes, Martingales, Stochastic calculus, Fitting models for data, Reliability and survival analysis, Functional data analysis, Discriminant and Regression Analysis, Mixture model and Probabilistic approach to Clustering, Analysis of complex data (incomplete, censored, missing, spatio-temporal, imprecise, fuzzy, ...), Data and Text Mining, Chaotic and Stochastic processes, Analysis of Chaotic processes, Neural Networks, Genetic and Fuzzy Algorithms, Support Vector Machine, Monte Carlo Methods, Chaotic Simulation.

Since its inception in 1985, AISTATS has been an interdisciplinary gathering of researchers at the intersection of artificial intelligence, machine learning, statistics, and related areas.

Neural Networks and Artificial Intelligence, Machine Learning,    Soft Computing, Evolutionary Computation, Metaheuristic Optimization, Fuzzy Logic

EURO Working Group on Stochastic Modelling / Politecnico di Milano

StochMod - the biennial meeting of the EURO Working Group on Stochastic Modelling - is the premier European forum for researchers who have an interest in stochastic modelling. Its eight edition will take place in Milan, at Politecnico di Milano.

The conference will be hosted and co-sponsored by Aalto University in cooperation with the University of Helsinki, Technical Research Centre of Finland, VTT and Radiation and Nuclear Safety Authority.

The Society for Risk Analysis – Europe invites you to its 29th Annual Conference at the Aalto University campus, Espoo, Finland, June 14-17, 2020 with the general subject “The Discipline(s) of Risk Science”. We welcome contributions from all areas of risk analysis and science, including risk assessment, risk characterization, risk perception, risk communication, risk management, risk governance and policy, relating to risks which are of concern to individuals, organizations in the public and private sector, or to society at local, regional, national, or global levels.

American Statistical Association

ICES has been running for more than 20 years. Information about its origins and development was included in the introduction to the December 2014 special issue of the Journal of Official Statistics, which presented papers from ICES-IV.

Methods and Practices for Statistics on Businesses, Farms, and Institutions

We are pleased to announce that the next International Symposium on Nonparametric Statistics will be held in Paphos, Cyprus, from 15-19 June 2020. In the tradition of the successful ISNPS conferences in Chalkidiki (2012), Cadiz (2014), Avignon (2016) and Salerno (2018), this meeting will bring together new and established researchers to consider a broad range of topics from nonparametric and semiparametric statistics. The program will include plenary lectures, invited and contributed talks, and posters.

Centre International de Rencontres Mathématiques (CIRM)

The 19th International Symposium on Dynamic Games and Applications, a four day conference, will be held in Porto, Portugal, June 16-19, 2020. The four day technical program will consist of plenary sessions, invited sessions, and presentations of contributed papers in several topics on Game Theory and its Applications. The International Symposium on Dynamic Games and Applications is a biennial professional event. The first one was held in 1984 in Haifa, Israel. It was followed by meetings in Williamsburg, USA (1986), Antibes, France (1988), Espoo, Finland (1990), Grimentz, Switzerland (1992), St. Jovite, Canada (1994), Kanagawa, Japan (1996), Maastricht, The Netherlands (1998), Adelaide, South Australia (2000), St. Petersburg Russia (2002), Tucson, USA (2004), Sophia Antipolis, France (2006), Wroclaw, Poland (2008), Banff, Canada (2010), Byšice, Czech Republic (2012), Amsterdam, the Netherlands (2014), Urbino, Italy (2016), Grenoble, France (2018).

Email: aapinto@fc.up.pt

Dynamic games and applications; Mean-field games; Repeated games; Stochastic games; Learning and adaptive games; Mechanism design; Evolutionary games; Cooperative equilibria; H-infinity control and robust controller designs; Theory of optimal control and dynamic games; Numerical methods and computer implementation of game models; Dynamic bargaining; Pursuit-Evasion games; Dynkin's game and its applications; Search, encounter and inspection games; Application of dynamic games in fields such as networking (telecommunications, transportation...); economics and finance; management and marketing; environment, energy and resource management; biology; social sciences;

The International Statistical Ecology Conference is a biennial meeting of researchers at the interface between ecology and statistics. At ISEC2020 we are planning an exciting list of keynote speakers that bridge these two disciplines, as well as providing attendees with training opportunities

Applied Mathematics (in general),    Ecosystems, Environment and Sustainable Development

Bernoulli Center (CIB)

Important classes of functional data, such as random measures and random operators, are intrinsically constrained and need to be represented as elements of suitable non-Euclidean spaces, such as Hilbert manifolds. The interplay between the infinite dimensionality of their variation and the non-linearity of their representation space poses novel challenges for statistics, at the interface of several domains, such as shape analysis, stochastic geometry, manifold learning, and functional data analysis. This workshop will bring together experts from these fields to explore these novel challenges and future perspectives.

Part of the Semester : Functional Data Analysis

IWFOS 2020 is jointly organized by Faculty of Science, Masaryk University, Brno, by Faculty of Mathematics and Physics, Charles University, Prague, and by The Union of Czech Mathematicians and Physicists, Brno branch.

The purpose of the series of IWFOS initiated by the working group STAPH of Toulouse at year 2008, is to highlight the major trends in different areas of functional statistics through the exchange of ideas and the promotion of collaboration between researchers from different countries. It aims at contributing to future developments of such areas. The workshop will be a platform for communication, exchange of ideas and interaction for researchers in statistics for infinite-dimensional and high-dimensional problems.

Institute of Mathematics, Faculty of Science, P. J. Šafárik University, Košice

The purpose of the meeting is to bring together researchers sharing an interest in a variety of aspects of statistics and its applications as well as matrix analysis and its applications to statistics, and offer them a possibility to discuss current developments in these subjects. The conference will mainly focus on a number of topics. The topics that have been selected so far include estimation, prediction and testing in linear models, robustness of relevant statistical methods, estimation of variance components appearing in linear models, generalizations to nonlinear models, design and analysis of experiments, including optimality and comparison of linear experiments, and applications of matrix methods in statistics.

Johannes Kepler University (JKU) and the Johann Radon Institute for Computational and Applied Mathematics (RICAM), in Linz, Austria

The Seventh International Conference on Uniform Distribution Theory (UDT 2020) will take place at the Johannes Kepler University (JKU) and the Johann Radon Institute for Computational and Applied Mathematics (RICAM), in Linz, Austria, in July 2020. Linz is the third-largest city of Austria and capital of the state of Upper Austria. Both JKU and RICAM are hosting institutions of the Special Research Program "Quasi-Monte Carlo Methods: Theory and Applications" funded by the Austrian Science Fund, FWF.

This conference brings together four leading statistical communities in the region – the Statistical Society of Australia, the New Zealand Statistical Association, the International Institute of Business Analysis (Special Interest Group for Business Analytics), and the Australian Conference on Teaching Statistics. The aim of this conference is to bring together a broad range of researchers and practioners across a variety of statistical disciplines to facilitate the exchange of theory, methods and applications. With these four societies working together there will be strong program components of interest to a wide diversity of academic, government, and industry colleagues. This includes the full spectrum of delegates from those advancing theoretical methodology to those working on industry applications (in traditional and non-traditional statistical areas). Of particular interest is how Big Data continues to impact all of us.

American Statistical Association

Scientific Computing ,    Modeling and Simulation

Bernoulli Society, Institute of Mathematical Statistics (IMS)

IMS Annual Meeting

S+SSPR 2020 is a joint biannual event organized by Technical Committee 1 (Statistical Pattern Recognition Technique) and Technical Committee 2 (Structural and Syntactical Pattern Recognition) of the International Association of Pattern Recognition (IAPR). Following the trend of previous editions, S+SSPR 2020 will be held in close proximity and shortly before the International Conference on Pattern Recognition (ICPR).

Centre International de Rencontres Mathématiques (CIRM)

Algebra,    Analysis

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Centre International de Rencontres Mathématiques (CIRM)

RESEARCH SCHOOL

Analysis,    Modeling and Simulation

CIRM – Centre International de Rencontres Mathématiques

The goal of this conference is to promote recent advances in Numerical Analysis related to Stochastic Partial Differential Equations and/or random processes and their applications. It covers various domains from simulation and analysis of numerical methods for PDE, SDE or SPDE, to propagation of uncertainty and the development of efficient simulation methods for random processes.

Numerical Analysis and Computational Mathematics,    Calculus, Differential Equations and Integration

CIRM – Centre International de Rencontres Mathématiques

INTERFACE PROGRAM (CIRM-INDUSTRY)

Modeling and Simulation,    Applied Mathematics (in general)

CIRM – Centre International de Rencontres Mathématiques

Center for Advanced Research for Applied Mathematics and Statistics, Manipal Academy of Higher Education, (MAHE)

Matrix Analysis, Projectors in Linear Models & Multivariate Analysis, Growth Curve Models, Linear Regression Models, Linear Statistical Inference, Modelling Covariance Structures, Multivariate and Mixed Linear Models, Statistics in Big Data Analysis.

Institute for Mathematical Sciences/National University of Singapore

The program aims at studying emerging questions on game theory and applications thereof. Some of the most relevant topics of investigation in game theory revolve around the idea of solution concept for a game, the complexity of its calculation, the ability of agents to learn it, its efficiency, and its nature when the game must satisfy some constraints, such as the ones imposed by an underlying network structure.

Pattern Recognition and Image Processing, Machine Vision,    Complex Networks

This is the third event of a series of conferences featuring talks by leading researchers in the three areas who are also capable of conveying their message to the audience coming from various regions of these fields. Beside the leading senior figures we also invite as speakers a smaller number of younger colleagues who have already shown their lion's claws.

Email: pad21-conference@bristol.ac.uk

Probability, Analysis, Dynamical systems

Analysis,    General Mathematical Research and Multidisciplinary Events

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Department of Mathematics & Statistics and the Department of Supply Chain & Business Technology Management of Concordia University in Montreal

In keeping with the long tradition of previous decennial conferences (starting in 1971), this convention is dedicated to all areas of statistical sciences. In addition to the traditional theoretical/applied areas, interdisciplinary research would be encouraged and promoted including major theme areas Applied Statistics, Big Data, Bioinformatics, Biostatistics, Computational Statistics, Data Mining, Data Science, Demography, Econometrics, Health Statistics, Model Selection and Validation, Social Statistics, Supply Chain, Survival Analysis, Stochastic Methods in Ecology, Finance and Engineering.

American Statistical Association

CIRM – Centre International de Rencontres Mathématiques

Since 1978, the ANS biennial international conference on Probabilistic Safety Assessment and Analysis has been a forum for communication of major probabilistic risk and safety topics worldwide, including issues, methods, applications, insights, policy, research, and risk-informed regulation experience.

CIRM – Centre International de Rencontres Mathématiques

Neural Networks and Artificial Intelligence, Machine Learning,    Algorithms

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

CIRM – Centre International de Rencontres Mathématiques

CIRM – Centre International de Rencontres Mathématiques

American Statistical Association

American Statistical Association

American Statistical Association

American Statistical Association