Conférences  >  Mathématiques  >  Statistique, Théorie des jeux  >  États-Unis

Institute for Computational and Experimental Research in Mathematics (ICERM)

This workshop focuses on connections between higher-order statistics and symmetric tensors, and their applications to machine learning, network science, and other domains. Higher-order statistics refers to the study of correlations between three or more covariates. This is in contrast to the usual mean and covariance, which are based on one and two covariates. Higher-order statistics are needed to characterize complex data distributions, such as mixture models. Symmetric tensors, meanwhile, are multi-dimensional arrays. They generalize covariance matrices and affinity matrices and can be used to represent higher-order correlations. Tensor decompositions extend matrix factorizations from numerical linear algebra to multilinear algebra. Recently tensor-based approaches have become more practical, due to the availability of bigger datasets and new algorithms. The workshop brings together applied mathematicians, statisticians, probabilists, machine learning experts, and computational algebraic geometers. Presentations will expose how symmetric tensors, with nonlinear algebra and non-convex optimization, provide natural mathematical machinery for exploiting higher-order interactions. Topics include moment tensor decompositions; spectral methods for hypergraphs; and related random matrix theory.

Email.: info@icerm.brown.edu

Mathématiques appliquées (en général),    Algèbre

Eastern North American Region International Biometric Society (ENAR)

Seminar on Stochastic Processes has the status of Permanent Co-sponsored Meeting of the Institute of Mathematical Statistics.

Seminar on Stochastic Processes is a series of annual conferences devoted to stochastic analysis, Markov processes and other topics in probability theory of current interest. Every conference features five invited speakers and provides opportunity for short informal presentations of recent results and open problems.

Institute for Pure and Applied Mathematics (IPAM)

The interplay of integrable models of statistical mechanics with combinations of probability theory and algebraic methods such as transfer matrix formalism, diagram algebras, and quantum group techniques, has proved fruitful in the past decades in both mathematics and physics. It has been particularly beneficial to enhance interactions between researchers working at the interfaces of these areas. The aim of this workshop is to bring together experts in algebraic and probabilistic aspects of solvable lattice models as well as researchers working on related algebraic subjects who have a common interest in understanding universal phenomena such as KPZ behavior, limit shapes, and convergence of lattice models to CFT predictions. In particular, we aim to develop interactions between different approaches to the study of lattice models, such as Bethe ansatz, (inhomogeneous) CFT methods and the tangent method. Other topics of potential interest include multi-species, forest fires and sandpile models, for which such interactions are less developed as for now. We also intend to foster interactions between researchers studying quantum groups and CFT on the one hand and probabilists working on SLE/CLE topics on the other, hoping for a fruitful synthesis of ideas and techniques.

Department of Mathematics at Utah Valley University (UVU)

The International Workshop in Sequential Methodologies (IWSM) is a biennial conference that covers all aspects of sequential methodologies in statistics, applied mathematics, information theory, change point detection, and virtually any applications in mathematical finance, quality control, clinical trials, signal and image processing, and other related fields. The goal of the workshop is to bring together researchers and users from all areas of sequential methodologies. The presentations are not limited to the field of sequential analysis. Speakers from other areas of probability, statistics, and related areas are welcome.

American Statistical Association

Simons Laufer Mathematical Sciences Institute (SLMath)

Networks, graph driven algorithms, and dynamics on graphs such as epidemics, random walks and centrality measures all play a major role, both in our daily lives as well as many scientific and engineering disciplines. This introductory workshop will bring together experts and junior researchers in combinatorics, probability, and statistics to share a broad vision of major challenges and objectives, with a primary focus on models of random graphs and their limits, network inference, dynamic processes on networks and algorithms and optimization on random structures.

Network models and random graphs, statistcal learning and network inference, counting and sampling discrete structures, dynamics on networks, probabilistic analysis of network algorithms

American Statistical Association

American Statistical Association (ASA)