ABSTRACT In this talk, the recent development in global, local and integration-based meshless computational methods via the use of radial basis function (RBF) will be presented....

ABSTRACT While Big Data are high-volume, high-dimensional, and high complexity, they are typically concentrated on low-dimensional manifolds or can be represented by graphs, digraphs, etc....

Abstract Hidden Markov models and Markov random fields are traditional statistical models that has found many applications....

Abstract I will give a few examples, informed by my own readings and experiences, of how mathematics helpsscientists and the general public in their everyday lives....

ABSTRACT In this talk, I will first introduce the classical variational approach of image reconstruction for parallel magnetic resonance imaging and image segmentation for breast mammography radiol...

ABSTRACT In this talk, I will first introduce the classical variational approach of image reconstruction for parallel magnetic resonance imaging and image segmentation for breast mammography radiol...

Abstract We give a brief overview of the Maxell equations, which are the governing equations of electromagnetism....

ABSTRACT After the last financial crisis, model uncertainty attracted academics and practitioners’ attention....

Over the past few decades, a lot of attention has been drawn to large-scale streaming data analysis, where researchers are faced with huge amount of high-dimensional data acquired in a stream fashion....

ABSTRACT Since the late 1950s, research on the limiting spectral properties of large-dimensional random matrices has attracted considerable interest among mathematicians, probabilists, and statisti...