Statistical Learning and Data Science

Driven by a vast range of applications, data analysis and learning from data are vibrant areas of research. Various methodologies, including unsupervised data analysis, supervised machine learning, and semi-supervised techniques, have continued to develop to cope with the increasing amount of data collected through modern technology. With a focus on applications, this volume presents contributions from some of the leading researchers in the different fields of data analysis. Synthesizing the methodologies into a coherent framework, the book covers a range of topics, from large-scale machine learning to synthesis objects analysis.