Important Dates
Last Date of Paper Submission
31st Oct 2016
Notification of Acceptance
Starts from 31st Oct 2016
Camera Ready Copy
Starts from 20th Nov 2016
Special Session on “Transfer Learning and Evolutionary Computation
in Optimization (TLECO)”
Session Chair(s):
Publication
Hari Mohan Pandey, Amity University, India, [email protected] ,
9810625304
All accepted and registered
papers of this special session will
be published in Springer SIST
series.
Ankit Chaudhary, Truman State University, USA, [email protected]
** Indexing: The books of this series are
submitted to SCOPUS, EI-Compendex
and Springerlink.
Yudong Zhang, Nanjing Normal University, China, Research Scientist, MRI Unit,
Columbia University, USA, [email protected]
http://www.springer.com/series/8767
Theme of Session:
Submission Guidelines
1. Prospective authors are invited
to submit original research work
that falls within the scope of the
session. All submissions will be
thoroughly peer-reviewed by
experts based on originality,
significance and clarity.
2. Only papers presenting novel
research results or successful
innovative applications will be
considered for publication in the
conference proceedings.
3. Kindly ensure that your paper
is formatted as per Springer SIST
Template (not exceeding 8 pages
written in A4 size).
Registration
Please visit conference webpage
for registration and other details:
http://anits.edu.in/sci2017/
Data mining, machine learning, and optimization algorithms have achieved promises in many
real-world tasks, such as classification, clustering and regression. These algorithms can often
generalize well on data in the same domain, i.e. drawn from the same feature space and with
the same distribution. However, in many real-world applications, the available data are often
from different domains. For example, we may need to perform classification in one target
domain, but only have sufficient training data in another (source) domain, which may be in a
different feature space or follow a different data distribution. Transfer Learning aims to
transfer knowledge acquired in one problem domain, i.e. the source domain, onto another
domain, i.e. the target domain. Transfer learning has recently emerged as a new learning
framework and hot topic in data mining and machine learning.
Evolutionary computation techniques have been successfully applied to many real world
problems, and started to be used to solve transfer learning tasks. Meanwhile, transfer learning
has attracted increasing attention from many disciplines, and has been used in evolutionary
computation to address complex and challenging issues. The theme of this special session is
to transfer learning in evolutionary computation, covering ALL different evolutionary
innovative applications will be computation paradigms. The aim is to investigate both the
new theories and methods on how transfer learning can be achieved with different
evolutionary computation paradigms, and how transfer learning can be adopted in
evolutionary computation, and the applications of evolutionary computation and transfer
learning in real-world problems. Authors are invited to submit their original and unpublished
work to this special session.
Topics of Interest:
We invite original (un-published) research contributions based on the above mentioned theme, including following topics but
not limited to:
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Evolutionary supervised transfer learning
Evolutionary unsupervised transfer learning
Evolutionary semi-supervised transfer learning
Domain adaptation and domain generalization in evolutionary computation
Instance based transfer approaches in evolutionary computation
Feature based transfer learning in evolutionary computation
Parameter/model based transfer learning in evolutionary computation
Relational based transfer learning in evolutionary computation
Transfer learning in evolutionary computation for classification, regression and clustering
Hybridization of evolutionary computation and machine learning, information theory, statistics, etc.
Transfer learning in in evolutionary computation for real-world applications, e.g.text mining, image analysis,
recognition, video processing, network optimization, WiFi localization, etc.
Paper Submission Process:
Please submit your paper (in word/pdf format) at
email: [email protected]
with „Name of Special Session: ‟ mentioned in the subject line.
Program Committee:
Deepti Mehrotra, Amity University Uttar Pradesh, India
Ankit Chaudhary, Truman State University, USA
Yudong Zhang, Normal University, China
Arun Prakash Agarwal, Amity University Uttar Pradesh, India
Patricia Ryser-Welch, York Univrsity U.K.
Kokula Krihna Hari, Scientist ASDF, India
Ankur Choudhary, Amity University Uttar Pradesh, India
Raghav Mehra, BIT Muzaffarnagar, India
Shruti Gupta, Amity University Uttar Pradesh
Neha Garg, Graphic Era University, India
Shanu Sharma, Amity University Uttar Pradesh, India
Rishi Kumar, Amity University Uttar Pradesh, India
Jagdish Raheja, Central Electronic Research Institute and Machine Learning and Vision Lab Pillani
A SN Chakravarthy, JNTU Hyderabad
Jitendra Pandey, Middle East College, Oman
For any further queries related to this special session, please contact the session chairs at:
E-mail ID: [email protected]
Mobile No.: 09810625304
face