文件名称：Machine Learning, Optimization,Big Data_Third International Conference, MOD 2017
文件大小：45.21MB
文件格式：PDF
更新时间：2021-01-19 13:24:11
Machine Learning BigData
MOD is an international conference embracing the fields of machine learning, opti- mization, and data science. The third edition, MOD 2017, was organized during September 14–17, 2017 in Volterra (Pisa, Italy), a stunning medieval town dominating the picturesque countryside of Tuscany. The key role of machine learning, reinforcement learning, artificial intelligence, large-scale optimization, and big data for developing solutions to some of the greatest challenges we are facing is undeniable. MOD 2017 attracted leading experts from the academic world and industry with the aim of strengthening the connection between these institutions. The 2017 edition of MOD represented a great opportunity for professors, scientists, industry experts, and postgraduate students to learn about recent developments in their own research areas and to learn about research in contiguous research areas, with the aim of creating an environment to share ideas and trigger new collaborations. As chairs, it was an honor to organize a premiere conference in these areas and to have received a large variety of innovative and original scientific contributions. During this edition, six plenary lectures were presented: Yi-Ke Guo, Department of Computing, Faculty of Engineering, Imperial College London, UK. Founding Director of Data Science Institute Panos Pardalos, Department of Systems Engineering, University of Florida, USA. Director of the Center for Applied Optimization Ruslan Salakhutdinov, Machine Learning Department, School of Computer Science at Carnegie Mellon University, USA. Director of AI Research at Apple My Thai, Department of Computer and Information Science and Engineering, University of Florida, USA Jun Pei, Hefei University of Technology, China Vincenzo Sciacca, Cloud and Cognitive Division – IBM Rome, Italy There were also two tutorial speakers: Domenico Talia, Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica Università della Calabria, Italy Xin–She Yang, School of Science and Technology – Middlesex University London, UK Moreover, the conference hosted the second edition of the industrial session on “Machine Learning, Optimization and Data Science for Real-World Applications”: Luca Maria Aiello, Nokia Bell Labs, UK Pierpaolo Basile, University of Bari, Italy Carlos Castillo, Universitat Pompeu Fabra in Barcelona, Spain Moderator: Aris Anagnostopoulos, Sapienza University of Rome, Italy We received 126 submissions from 46 countries and five continents; each manu- script was independently reviewed by a committee formed by at least five members through a blind review process. These proceedings contain 49 research articles written by leading scientists in the fields of machine learning, artificial intelligence, rein- forcement learning, computational optimization, and data science presenting a sub- stantial array of ideas, technologies, algorithms, methods, and applications. For MOD 2017, Springer generously sponsored the MOD Best Paper Award. This year, the paper by Khaled Sayed, Cheryl Telmer, Adam Butchy, and Natasa Miskov-Zivanov titled “Recipes for Translating Big Data Machine Reading to Exe- cutable Cellular Signaling Models” received the MOD Best Paper Award. This conference could not have been organized without the contributions of these researchers, and so we thank them all for participating. A sincere thank you also goes to all the Program Committee, formed by more than 300 scientists from academia and industry, for their valuable work of selecting the scientific contributions. Finally, we would like to express our appreciation to the keynote speakers, tutorial speakers, and the industrial panel who accepted our invitation, and to all the authors who submitted their research papers to MOD 2017.