Tuesday, 16 October 2018

CFP: IEEE CEC 2019 Special Session on Data-Driven Evolutionary Optimization of Computationally Expensive Problems

Meta-heuristic algorithms, including evolutionary algorithms and swarm optimization, face challenges when solving time-consuming problems, as typically these approaches require thousands of function evaluations to arrive at solutions that are of reasonable quality. Surrogate models, which are computationally cheap, have in recent years gained in popularity in assisting meta-heuristic optimization, by replacing the compute-expense/time-expensive problem during phases of the heuristic search. However, due to the curse of dimensionality, it is very difficult, if not impossible to train accurate surrogate models. Thus, appropriate model management techniques, memetic strategies and other schemes are often indispensable. In addition, modern data analytics involving advance sampling techniques and learning techniques such as semi-supervised learning, transfer learning and active learning are highly beneficial for speeding up evolutionary search while bringing new insights into the problems of interest. This special session aims at bringing together researchers from both academia and industry to explore future directions in this field. 

Scope and Topics

The topics of this special issue include but are not limited to the following topics:

  • Surrogate-assisted evolutionary optimization for computationally expensive problems
  • Adaptive sampling using machine learning and statistical techniques
  • Surrogate model management in evolutionary optimization
  • Data-driven optimization using big data and data analytics
  • Knowledge acquisition from data and reuse for evolutionary optimization
  • Computationally efficient evolutionary algorithms for large scale and/or many-objective optimization problems
  • Real world applications including multi-disciplinary optimization.

Important Dates

Submission deadline:7 January 2019
Notification: 7 March 2019
Final paper submission: 31 March 2019
Early Registration: 31 March 2019


The papers must be submitted online through the manuscript submission system (http://cec2019.org/papers.html#submission). 


Prof. Chaoli Sun, Department of Computer Science and Technology, Taiywan University of Science and Technology, China. 

Prof. Jonathan Fieldsend, Department of Computer Science, University of Exeter, United Kingdom. 

Prof. Yew-Soon Ong, School of Computer Engenieering, Nanyang Technological University, Singapore. 

CFP: IEEE CEC 2019 Special Session on Memetic Computing

Memetic Computing (MC) represents a broad generic framework using the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving. In the literature, MC has been successfully manifested as memetic algorithm, where meme has been typically perceived as individual learning procedures, adaptive improvement procedures or local search operators that enhance the capability of population based search algorithms. More recently, novel manifestations of meme in the forms such as knowledge building-block, decision tree, artificial neural works, fuzzy system, graphs, etc., have also been proposed for efficient problem-solving. These meme-inspired algorithms, frameworks and paradigms have demonstrated with considerable success in various real-world applications.

The aim of this special session on memetic computing is to provide a forum for researchers in this field to exchange the latest advances in theories, technologies, and practice of memetic computing.

Scope and Topics

The scope of this special session covers, but is not limited to:

  • Single/Multi-Objective memetic algorithms for continuous or combinatorial optimization
  • Theoretical studies that enhance our understandings on the behaviors of memetic computing
  • Adaptive systems and meme coordination
  • Novel manifestations of memes for problem-solving
  • Cognitive, Brain, individual learning, and social learning inspired memetic computation
  • Self-design algorithms in memetic computing
  • Memetic frameworks using surrogate or approximation methods
  • Memetic automaton, cognitive and brain inspired agent based memetic computing
  • Data mining and knowledge learning in memetic computation paradigm
  • Memetic computing for expensive and complex real-world problems
  • Evolutionary multi-tasking

Paper Submission

Papers for IEEE CEC 2019 should be submitted electronically through the Congress website at http://cec2019.org/, and will be refereed by experts in the fields and ranked based on the criteria of originality, significance, quality and clarity. To submit your papers to the special session, please select the Special Session name in the Main Research topic.

For more submission information please visit: http://cec2019.org/
All accepted papers will be published in the IEEE CEC 2019 electronic proceedings, included in the IEEE Xplore digital library, and indexed by  EI Compendex. High quality papers will be invited to extend and submit to the Memetic Computing Journal.

Important Dates

Submission Deadline: January 7, 2019
Notification of Acceptance: March 7, 2019

CFP: IEEE Congress on Evolutionary Computation (CEC 2019)

The annual IEEE Congress on Evolutionary Computation is one of the leading events in the area of evolutionary computation. It covers all topics in evolutionary computation including, but not limited to the following areas:

  • Artificial life
  • Agent-based systems
  • Artificial immune systems
  • Bioinformatics and bioengineering
  • Coevolution and collective behavior
  • Combinatorial and numerical optimization
  • Constraint and uncertainty handling
  • Cognitive systems and applications
  • Computational finance and economics
  • Estimation of distribution algorithms
  • Evolvable adaptive hardware and systems
  • Evolutionary data mining
  • Evolutionary design
  • Evolutionary learning systems
  • Evolutionary game theory
  • Evolutionary multi-objective optimization
  • Evolutionary scheduling
  • Industrial applications of EC
  • Particle Swarm Optimization
  • Representation and operators

IEEE CEC 2019 is a world-class conference that brings together researchers and practitioners in the field of evolutionary computation and computational intelligence from around the globe. Technical exchanges within the research community will encompass keynote lectures, regular and special sessions, tutorials, and competitions, as well as poster presentations. In addition, participants will be treated to a series of social functions, receptions, and networking events to establish new connections and foster everlasting friendship among fellow counterparts.

Important Dates:

  • Special session proposals: 26 October, 2018
  • Competition proposals: 26 November, 2018
  • Workshop proposals: 7 January, 2019
  • Tutorial proposals: 7 January, 2019
  • Paper submission: 7 January, 2019
  • Decision notification: 7 March, 2019
  • Camera ready paper due: 31 March, 2019
  • Registration: 31 March, 2019
  • Conference: 10 June, 2019

Note: all deadlines are 11:59pm US pacific time.

Further Information: http://www.cec2019.org/

Thursday, 11 October 2018

Call for participation: Indigenous Language Technologies at the CoEDL Summer School, ANU Canberra, Australia (Nov 26-30)

Date: 26 - 30 November 2018

Venue: Australian National University, Canberra

The Centre’s annual Summer School is a flagship educational event on Australia’s linguistics calendar. Over the course of five days, we bring together leading national and international scholars to present the latest research in the field through intensive ‘deep dives’ across the multi-disciplinary breadth of the science of languages.
Summer School draws on expertise across the Centre’s programs, member universities and international partners to provide intensive training, enrich existing knowledge and catalyse new research collaborations. Participants range from advanced undergraduate students through to senior academics. Many of the courses require no previous knowledge or experience, only a burning curiosity about the dynamics of the world’s many and greatly varied languages.
This year’s Summer School will have a dual focus on the intersection of language and technology, and community engagement. Aspiring linguists, as well as students with backgrounds in engineering, AI and computer science, will have an opportunity to learn about computational linguistics and natural language processing, including practical, hands-on sessions using the latest software tools and practices. Prominent researches will bring their extensive insights and experience from the field working with Australian and other indigenous communities to document, study and revitalise their languages.
The 2018 Summer School program offers courses in streams over four days (Monday, Tuesday, Thursday and Friday). Each course consists of four 1.5 hour sessions over the four days and will have the same timeslot each day. 
Beginning with a daily masterclass on the foundations of language by Professor Stephen Levinson,  the program offers twelve courses, each delivered over four days. Other highlights include Professor Nick Evans’ popular linguistic field methods course on an Australian language, and Professor Leanne Hinton imparting a lifetime of knowledge on working as an academic with indigenous communities. Meanwhile Google’s Daan van Esch will need two sessions per day to get his students fully up to date with the latest tech in machine learning and automatic speech recognition.
Summer Schools have become famous for building a community of interest across the many disciplines of language science – and this year will be no different. We break up the intensive course program up on the Wednesday  with optional workshops on lighter topics, discussion sessions, opportunities for networking, and of course – a busy social calendar as well.
Public Lectures
On the evening of 27 November, the Centre is proud to present Dr Alpheaus Graham Zobule, Founder and Director of Kulu Language Institute of the Solomon Islands, who will recount a decades-long project that has allowed speakers of a vernacular tongue (Luqa) to study their own language in that language – an inspirational story of teaching literacy to strengthen an indigenous language.
On 29 November, blogger, podcaster and linguistic communicator extraordinaire Gretchen McCulloch will regale and dazzle her audience on the linguistics of the internet. Informal written language - the sort found in text messages and social media post - can answer some longstanding questions, such as where to draw the boundaries on dialect maps. And new ones, such as how people are using emoji and punctuation to give writing a sense of gesture and tone of voice. 
Summer School 2018 registrations are open. until Monday 19 November.
At just $300 for students and the unwaged (and $400 for others), the registration fee for Summer School has been intentionally set to give access to this special learning experience to the broadest possible spectrum of participants.
Please also use the registration form to sign up for the Summer School Dinner, other social events, and the two free public lectures.
We have secured affordable four, five and six night accommodation options on the ANU campus for those travelling to Canberra, which may be booked when registering. The accommodation is available on campus to book and will be paid as part of your main registration payment. 


For more information contact: coedlevents@anu.edu.au

Friday, 5 October 2018

Call for submissions: IEEE Computational Intelligence Society Webinar Competition 2018

Emerging Topics and Applications of Computational Intelligence

Topics Include: Deep Learning, computational neuroscience, Brain Computer Interface, ambient intelligence, CI approaches to natural language, artificial life, cultural learning, computational intelligence for the IoT, Smart-X technologies, legal, ethical and social impacts of CI, Internet of Things, Big Data and Big Knowledge

Prizes 1st prize  -  $500 USD, 2nd prize -  $300 USD, 3rd prize  -  $200 USD

Important Dates: 
Opening Date: 1st  July 2018  Closing Date: 1st  November 2018

Announcement of Winners:  Awards Ceremony at IEEE SSCI 2018, India
You will be required to submit a Webinar Title, Abstract, a URL to  webinar (maximum 30 minutes).  The webinar can be submitted as an URL to *any* repository e.g. (YouTube, Youku, BiliBili, Dropbox, Github, Google Drive, etc...).

CFP: IEEE CIM Special Issue on CI for Internet of Things in the Big Data Era (Dec 31)


Emerging Internet of Things (IoT) applications in various fields, including smart city, smart home, smart grid, e-health, smart transportation, computer vision applications, etc., critically require trustworthy networking solutions that are resilient against disturbances and disruptions, including high mobility, high density, disasters, infrastructure failures, cyberattacks, and other disruptions. The networking framework should be capable of providing more secure, reliable and efficient communications in various network environments, especially for the performance-sensitive and mission-critical applications such as remote surgery and autonomous driving.
Two main challenges exist in enforcing trustworthy IoT. The first challenge comes from the spatial diversity of the entities involved in communications, such as the high mobility of the devices, and the limitations of propagation media and other resources. The second challenge is due to the varying temporal features of the environment. Due to the spatial challenges, the connectivity between network nodes could be unreliable, and therefore the information maintained at each node could be inaccurate, which requires trustworthy solutions that are able to handle the dynamic, imprecise and uncertain information. This can be solved by using computational intelligence (CI) technologies such as fuzzy logic and evolutionary computation. On the other hand, Big Data-based approaches, including deep neural networks, could facilitate data-driven prediction and performance improvement by capturing time-dependent properties of network elements such as user traffic and behaviors. However, the IoT data can be highly dimensional, heterogeneous, complex, unstructured and unpredictable. The integration of two new technologies, namely IoT and Big Data, gives birth to a novel ecosystem, conveniently called IoT Big Data, which calls for novel CI technologies to provide efficient and powerful tools that scale well with massive data volume analytics and processes, while addressing the challenges brought by the massive amount of data. In short, while CI technologies can achieve a flexible and self-evolving system design, Big Data can facilitate the use of deep neural networks through which learning the best strategy from complex data becomes possible.
This special issue will focus on the technical challenges and the synergistic effect of Big Data and CI for trustworthy IoT. It is envisioned that the combination of Big Data with a large collection of CI algorithms will reach the level of true artificial intelligence in IoT. We invite researchers to contribute their original research articles that will facilitate the development of IoT based on CI and big data technologies, including (but not limited to):
  • Artificial neural networks for IoT Big Data
  • CI for trustworthy IoT
  • CI for mobile edge computing
  • CI for wireless networking
  • CI for security in IoT systems
  • CI for sensor and actuator networks
  • CI for IoT applications
  • Convolutional neural networks for IoT
  • Crowdsourced learning for IoT
  • Data-driven IoT with CI
  • Deep neural networks for trustworthy IoT
  • Deep reinforcement learning for IoT
  • Development of CI for IoT environments
  • Domain adaptation for IoT Big Data
  • Evolutionary computing for IoT Big Data
  • Evolutionary models for IoT Big Data
  • Fuzzy logic for IoT Big Data
  • Learning theory for IoT Big Data
  • Machine learning for IoT Big Data
  • Probabilistic methods for IoT Big Data
  • Recurrent neural networks for IoT
  • Sequence-to-sequence learning for IoT Big Data 

Submission Deadline: December 31st, 2018
Notification of the First Review Results: March 15th, 2019
Submission of Revised Manuscripts: April 15th, 2019
Notification of Second Review Results: May 15th, 2019
Submission of Final Manuscript: June 15th, 2019
Special Issue Publication: November 2019 Issue

Dr. Celimuge Wu, The University of Electro-Communications, Japan, celimuge@uec.ac.jp
Dr. Guoliang Xue, Arizona State University, USA, xue@asu.edu
Dr. Jie Li, University of Tsukuba, Japan, lijie@cs.tsukuba.ac.jp
Dr. Kok-Lim Alvin Yau, Sunway University, Malaysia, koklimy@sunway.edu.my
Dr. Junaid Qadir, Information Technology University, Pakistan, junaid.qadir@itu.edu.pk

1. The IEEE Computational Intelligence Magazine requires all prospective authors to submit their manuscripts in electronic format, as a PDF file. The created PDF file must be a single file for the complete submitted paper, including figures and bibliography. Before the manuscript is submitted, prospective authors should make sure that the PDF file is (1) printable, and (2) its first page contains the title, authors' names and the corresponding author's email address, abstract, and up to 5 keywords. Additional information about submission guidelines and information for authors is provided at the IEEE CIM website. Submission should be made via https://easychair.org/conferences/?conf=ieeecimsiiot2019.
2. Send also an email to guest editor C. Wu (celimuge@uec.ac.jp) with subject “IEEE CIM special issue submission” to notify about your submission.
3. Early submissions are welcome. We will start the review process as soon as we receive your contribution.

CFP: IEEE TETCI Special Issue on Privacy and Security in Computational Intelligence (Nov 30)


  The advance in the state-of-the-art computing paradigms and infrastructure such as cloud computing, Internet of Things (IoT) and their fusion fog computing, has enabled a variety of large-scale applications where big data are collected, transmitted, stored, processed and mined. Unlocking the value of the data plays the key role in the data lifecycle. Computational intelligence (CI) technologies are an effective and important way to extract the intelligence and knowledge from datasets for data-driven decision-makings. Given that CI methods are usually both data- and computation-intensive, leveraging the large-scale computing paradigms and infrastructure empowers CI methods to handle data at a very large scale for deeper or personalized intelligence and insights. A typical example is the recent boom of deep learning research which is significantly enhanced by the development of massive computational power.
  However, the characteristics of the state-of-the-art computing paradigms and infrastructural platforms, such as ubiquitous access and multi-tenancy, pose unprecedented privacy and security threats on the computing infrastructure for CI and the application of CI in real problems, rendering users more vulnerable to privacy leakage and security attacks. It is necessary to keep privacy and security concerns in mind when implementing hardware (e.g., Intel’s neural networks processor instructions) and platforms for CI, designing CI algorithms, and deploying CI applications. Hence, it is the high time to investigate the privacy and security issues related to CI in the era of big data and cloud/fog computing.
  This special issue aims to present the most recent advances in the privacy and security research related to CI, particularly in (1) secure and privacy hardware and platforms to support CI technologies, (2) innovative secure and privacy CI algorithms for data mining and knowledge discovery, as well as (3) novel CI methods that strengthen privacy and security technologies.


  Potential topics of interest for this special issue include, but are not limited to:
  • Secure and large-scale systems and platforms supporting computational intelligence paradigms
  • Privacy-preserving and anonymization technologies for computational intelligence
  • Computational intelligence paradigm implementation across private/public computing systems/platforms
  • Information security and privacy theories from computational intelligence perspectives
  • Computational intelligence techniques for cyberspace intrusion detection systems
  • Computational intelligence for digital forensics
  • Computational intelligence for risk management
  • Computational intelligence for data-driven cyberspace security and information privacy
  • Real-world applications of computational intelligence for privacy and security


Manuscripts should be prepared according to the“Information for Authors” section of the journal(http://cis.ieee.org/ieee-transactions-on-emerging-topics-in-computational-intelligence.html) and submissions should be done through the journal submission website: https://mc.manuscriptcentral.com/tetci-ieee, by selecting the Manuscript Type of Privacy and Security in Computational Intelligence” and clearly marking “Privacy and Security in Computational Intelligence Special Issue Paper” as commentsto the Editor-in-Chief. Submitted papers will be reviewed by at least three different reviewers. Submission of a manuscript implies that it is the authors’ original unpublished work and is not being submitted for possible publication elsewhere.


  • Paper submission deadline: November 30, 2018
  • Notice of the 1st round review results: March 01, 2019
  • Revision due: May 31, 2019
  • Final notice of acceptance/reject: August 30, 2019