-------- Forwarded Message --------
Apologies for possible cross posting
---------------------- Call for Papers Call for Papers - Deadline
Extended (Firm) 23 April 2019----------------------------
The International Conference on Deep Learning and Machine Learning
in Emerging Applications (Deep-ML 2019)
26-28 August 2019, Istanbul, Turkey
http://www.ficloud.org/deep-ml-2019/
<http://www.ficloud.org/deep-ml-2019/>
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Deep learning and machine learning are the state-of-the-art at
providing models, methods, tools and techniques for developing
autonomous and intelligent systems which can revolutionize
industrial and commercial applications in various fields such as
online commerce, intelligent transportation, healthcare and
medicine, security, manufacturing, education, games, and various
other industrial applications. Google, for example, exploits the
techniques of deep learning in voice and image recognition
applications, while Amazon uses such techniques in helping
customers in their online purchase decisions.
The International Conference on Deep Learning and Machine Learning
in Emerging Applications (Deep-ML) provides a leading forum for
researchers, developers, practitioners, and professional from
public sectors and industries in order to meet and share latest
solutions and ideas in solving cutting edge problems in modern
information society and economy.
The conference comprises a set of tracks that focus on specific
challenges in deep learning and machine learning and their
applications in emerging areas. Topics of interest include, but
are not limited to, the following:
1) Deep and Machine Learning Models and Techniques:
Novel machine and deep learning
Active learning; Incremental learning and online learning
Agent-based learning; Manifold learning Multi-task learning
Bayesian networks and applications
Case-based reasoning methods
Statistical models and learning
Computational learning; Evolutionary algorithms and learning
Evolutionary neural networks
Fuzzy logic-based learning
Genetic optimization
Clustering, classification and regression
Neural network models and learning
Parallel and distributed learning
Reinforcement learning
Supervised, semi-supervised and unsupervised learning
Tensor Learning
2) Deep and Machine Learning for Big Data Analytics:
Deep/Machine learning based theoretical and computational models
Novel techniques for big data storage and processing
Data analysis, insights and hidden pattern
Data analysis and decision making
Data wrangling, munching and cleaning
Data integration and fusion
Data visualization
Data and information quality, efficiency and scalability
Security threat detection using big data analytics Visualizing
security threats Enhancing privacy and trust
Data analytics in complex applications – finance, business,
healthcare, engineering, medicine, law, transportation, and
telecommunication
3) Deep and Machine Learning for Data Mining and Knowledge:
Data mining in the web and online systems
Multimedia; images and video data mining
Feature extraction and classification
Information retrieval and extraction
Distributed and P2P data search
Sentiment analysis
Mining high velocity data streams
Anomaly detection in streaming data
Mining social media and social networks
Mining sensor and computer networks data
Mining spatial and temporal datasets
Data classification, clustering, and association
Knowledge acquisition and learning
Knowledge representation and reasoning
Knowledge discovery in large datasets
4) Deep and Machine Learning Application Areas:
Bioinformatics and biomedical informatics
Finance, business and retail
Intelligent transportation Healthcare, medicine and clinical
decision support
Computer vision
Human activity recognition
Information retrieval and web search
Cybersecurity
Natural language processing
Recommender systems
Social media and networks
5) Deep and Machine Learning for Computing and Network Platforms:
Network and communication systems
Software defined networks
Wireless and sensor networks
Internet of Things (IoT)
Cloud Computing
Edge and Fog Computing
Paper Submission:
Full papers must be in English and should be between 12 to 14
pages. Short papers should be limited to 8 pages. Papers must be
formatted in Springer's LNCS format.
Submitted research papers may not overlap with papers that have
already been published or that are simultaneously submitted to a
journal or a conference with proceedings.
Important Dates:
Submission Deadline (Extended - Firm): 23 April 2019
Authors Notification: 20 May 2019
Final Manuscript Due: 14 June 2019
ORGANISING COMMITTEE
General Co-Chairs:
Joao Gama, University of Porto, Portugal
Edwin Lughofer, Johannes Kepler University Linz, Austria
Program Co-Chairs:
Irfan Awan, University of Bradford, UK
Hadi Larijani, Glasgow Caledonian University, UK
Local Organising Co-Chairs:
Perin Ünal, Teknopar, Turkey
Sezer Gören, Ugurdag Yeditepe University, Turkey
Tacha Serif, Yeditepe University, Turkey
Publication Chair:
Muhammad Younas, Oxford Brookes University, UK
Journal Special Issue Coordinator:
Lin Guan, Loughborough University, UK
Workshop Coordinator:
Filipe Portela, University of Minho, Portugal
Publicity Chair:
Esra N. Yolaçan, Osman Gazi University, Turkey
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