Machine Learning and Data Analytics Symposium - MLDAS 2017
The Fourth Machine Learning and Data Analytics (MLDAS) Symposium, will be held on March 13-14, 2017 at the Qatar National Convention Centre in Doha, Qatar.
Submissions to MLDAS 2017 are due by February 12, 2017 at 11:59pm Pacific Standard Time.
The submissions page is here.
We would like to invite authors to send in contributed submissions - FULL papers or POSITION papers - on any of the topics of interest of the symposium: machine learning, data mining, applied machine learning techniques, data analytics solutions.
Registration for MLDAS 2017 is open.
Background and Objectives
The purpose of this symposium is to bring together researchers, practitioners, students, and industry experts in the fields of machine learning, data mining, and related areas to present recent advances, to discuss open research questions, and to bridge the gap between data analytics research and industry needs on certain concrete problems.
The MLDAS symposium will serve as a platform for exchange of ideas, identification of important and challenging applications, and discovery of possible synergies.
We will address the topics of interest through both invited and contributed talks describing (1) research ideas, (2) new challenges, (3) mature research and (4) practical results. The symposium program will consist of presentations by invited speakers of both industry and academia, and by the authors of the papers submitted to the symposium. In addition, we will have a panel discussion to identify important research problems and applications.
The MLDAS symposium will take place on March 13 and March 14, 2017.
MLDAS is co-chaired by Sanjay Chawla (QCRI), Dragos Margineantu (Boeing Research & Technology) and Mohammed Zaki (RPI).
To contact the MLDAS symposium organizers on any matter, please check this page.Registration for MLDAS 2017 is open. Researchers, students, and practitioners interested in attending the symposium, should register via the registration page.
|MLDAS 2017 - Doha, Qatar|