The International Conference on Machine learning, Optimization, and big Data (MOD) has established itself as a premier interdisciplinary conference in machine learning, computational optimization, knowledge discovery and data science. It provides an international forum for presentation of original multidisciplinary research results, as well as exchange and dissemination of innovative and practical development experiences.
The conference will consist of four days of conference sessions. We invite submissions of papers on all topics related to Machine learning, Optimization, Knowledge Discovery and Data Science including real-world applications for the Conference Proceedings (Springer ? Lecture Notes in Computer Science -LNCS).
Topics of Interest
The last five-year period has seen a impressive revolution in the theory and application of machine learning, optimization and big data.
Renato Umeton, Harvard University, USA
Giovanni Giuffrida, University of Catania, Italy & Neodata Group
Giuseppe Nicosia, University of Catania, Italy
Panos Pardalos, University of Florida, USA
Special Session Co-Chairs:
Giuseppe Narzisi, New York University Tandon School of Engineering & New York Genome Center, New York, USA
Piero Conca, CNR, Italy
Industrial Panel Chairs:
Ilaria Bordino, Marco Firrincieli, Fabio Fumarola, and Francesco Gullo, UniCredit R&D