Machine Learning on Big Data
(MLBD 2019)
in conjunction with
2019 IEEE International Conference
on Big Data (IEEE BigData 2019)
December 9-12, 2019, Los Angeles, CA, USA
[Aim and Scope | Session
Location | Submission Guidelines and
Instructions | Paper Publication | Important
Dates | Program Committee]
Best Papers of MLBD
2019 will be Invited for Extended Submission to a
Top-Quality Journal
The Special Session “Machine Learning on Big Data” (MLBD 2019)
of the 2019 IEEE
International Conference on Big Data (IEEE BigData
2019) follows the great success of three previous editions co-located with
the IEEE ICMLA conference series and focuses on machine learning models,
techniques and algorithms related to Big Data, a vibrant and challenging
research context playing a leading role in the Machine Learning and Data Mining
research communities. Big data is gaining attention from researchers, being
driven among others by technological innovations (such as cloud interfaces) and
novel paradigms (such as social networks). Devising and developing machine
learning models, techniques and algorithms for big data represent a fundamental
problem stirred-up by the tremendous range of critical applications
incorporating machine learning tools in their core platforms. For example, in
application settings where big data arise and machine is useful, we recognize,
among other things: (i) machine-learning-based processing (e.g., acquisition,
knowledge discovery, and so forth) over large-scale sensor networks introduces
important advantages over classical data-management-based approaches;
similarly, (ii) medical and e-heath information systems usually include
successful machine learning tools for processing and mining very large graphs
modelling patient-to-disease, patient-to-doctor, and patient-to-therapy
networks; (iii) genome data management and mining can gain important benefits
from machine learning algorithms. Some hot topics in machine learning on big data
include: (i) machine learning on unconventional big data sources (e.g.,
large-scale graphs in scientific applications, strongly-unstructured social
networks, and so forth); (ii) machine learning over massive big data in
distributed settings; (iii) scalable machine learning algorithms; (iv) deep
learning – models, principles, issues; (v) machine-learning-based predictive
approaches; (vi) machine-learning-based big data analytics; (vii)
privacy-preserving machine learning on big data; (viii) temporal analysis and
spatial analysis on big data; (ix) heterogeneous machine learning on big data;
(x) novel applications of machine learning on big data (e.g., healthcare,
cybersecurity, smart cities, and so forth).
The
MLBD 2019 special session focuses on all the research aspects of machine
learning on Big Data. Among these, an unrestricted list includes:
The
Special Session
“Machine Learning on Big Data” (MLBD 2019) of the 2019 IEEE
International Conference on Big Data (IEEE BigData
2019) will be held in Los Angeles, CA, USA, during
December 9-12, 2019, and it aims to synergistically connect the research
community and industry practitioners. It provides an international forum where
scientific domain experts and Machine Learning and Data Mining researchers,
practitioners and developers can share their findings in theoretical
foundations, current methodologies, and practical experiences on Machine
Learning on Big Data. MLBD 2019 will provide a stimulating environment to
encourage discussion, fellowship, and exchange of ideas in all aspects of
research related to Machine Learning on Big Data. This includes both original
research contributions and insights from practical system design,
implementation and evaluation, along with new research directions and emerging
application domains in the target area. An expected outcome from MLBD 2019 is
the identification of new problems in the main topics, and moves to achieve
consolidated solutions to already-known problems. Other goals are to help in
creating a focused community of scientists who create and drive interest in the
area of Machine Learning on Big Data, and additionally to continue on the
success of the event across future years.
The Westin Bonaventure Hotel & Suites, Los Angeles, CA,
USA
Submission Guidelines and Instructions
Contributions
are invited from prospective authors with interests in the indicated session
topics and related areas of application. All contributions should be high
quality, original and not published elsewhere or submitted for publication
during the review period.
Submitted
papers should strictly follow the IEEE official template. Maximum paper length allowed
is 10 pages.
Submitted
papers will be thoroughly reviewed by members of the
Special Session Program Committee for quality, correctness, originality and
relevance. All accepted papers must be presented by one of the authors, who
must register.
Papers must be submitted via the CyberChair System by selecting the track “Special
Session on Machine Learning on Big Data”.
Accepted
papers will appear in the proper Big Data 2019 proceedings, published by IEEE.
Authors of
selected papers from the workshop will be invited to submit an extended version
of their paper to a special issue of a high-quality international journal.
Paper
submission: September 15, 2019
Notification of acceptance: October 15, 2019
Camera-ready paper due: November 10, 2019
Alfredo Cuzzocrea,
University of Calabria, Italy
Program Committee
Michelangelo
Ceci, University of Bari, Italy
Alfredo Cuzzocrea, University of Trieste and ICAR-CNR, Italy
Joao Gama, University of Porto, Portugal
Marwan Hassani, TU Eindhoven, The Netherlands
Mark Last, Ben-Gurion University of the Negev, Israel
Rocco Langone, Deloitte, Belgium
Carson K. Leung, University of Manitoba, Canada
Sofian Maabout, LABRI, Bordeaux University, France
Anirban Mondal, Shiv Nadar
University, India
Enzo Mumolo, University of Trieste, Italy
Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece
For more information and any inquire, please contact Alfredo Cuzzocrea