The analysis of complex and massive data sets which display attributes of spatial and temporal characteristics is a growing field of research. Traditionally the two fields have been treated predominantly via a range of different approaches, depending on the discipline in which the applications are under study. For instance in spatial statistics and geo-statistics there is a long history of spatial modeling via regression models, random fields and parametric approaches. There is also a large literature on spatial extremes and the analysis of such features of spatial temporal data. In machine learning there are new approaches being considered based on semi-parametric and non-parametric modeling paradigms which incorporate Bayesian modeling. Then in the signal processing and engineering communities there have been a range of frequency and spatial methods developed based on filters, parametric modeling, regression - basis expansion models, wavelets regression models, and splines.
There has been a range of recent developments in characterizing multivariate spatial and temporal processes which are either discrete (branching and counting processes) or continuous (heavy tailed processes such as Levy processes) and their sub-families the stable processes and Gaussian processes. In addition the study of such processes in practical applications has advanced significantly and the intention of the workshops is to present some recent developments in specification, estimation in high dimensional and complex structured models formed from such processes and application.
In the workshop we aim to introduce these theory and methodology for a range of real applications in areas of machine learning, wireless communications, sensor networks, finance, insurance, earthquake dynamic modeling, environmental modeling, signal processing and speech and audio processing.
Conference Room 1 (2F), Institute of Statistical Mathematics, Tokyo, Japan
27 Feb 2018 (Tue) - 28 Feb 2018 (Wed)
- Prof. Matthew Ames (ISM)
- Prof. Nourddine Azzaoui (Université Clermont Auvergne)
- Ms. Holly Brannelly (UCL)
- Ms. Marta Campi (UCL)
- Prof. Jennifer S. K. Chan (University of Sydney)
- Prof. Laurent Clavier (IMT Lille Douai)
- Prof. Kenji Fukumizu (ISM)
- Prof. Norikazu Ikoma (NIT)
- Dr. Andrea Macrina (UCL)
- Prof. Konstantin Markov (Aizu U.)
- Prof. Tomoko Matsui (ISM)
- Prof. Daisuke Murakami (ISM)
- Prof. Tor André Myrvoll (SINTEF Digital)
- Dr. Ido Nevat (TUM CREATE)
- Prof. Gareth W. Peters (Heriot-Watt University)
- Prof. Francois Septier (IMT Lille Douai)
- Prof. Pavel Shevchenko (Macquarie University)
- Prof. Makoto Yamada (RIKEN AIP)
- Prof. Yoshiki Yamagata (National Institute for Environmental Studies)
- Mr. Hongxuan Yan (University of Sydney)
- Dr. Mari Yoshitaka (Mitsubishi UFJ Morgan Stanley Securities)
- Mr. Xiaoming Zhang (Bloomberg)
The working language of the conference is English.
The Institute of Statistical Mathematics (ISM)