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CD-MAKE 2020 - 4th International IFIP Cross Domain Conference for Machine Learning & Knowledge Extraction

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Category machine learning; knowledge extraction; artificial intelligence

Deadline: March 29, 2020 | Date: August 25, 2020-August 28, 2020

Venue/Country: University College Dublin, Ireland

Updated: 2020-01-29 17:09:58 (GMT+9)

Call For Papers - CFP

“Augmenting Human Intelligence with Artificial Intelligence”

Call for Papers - CD-MAKE 2020

4th International IFIP Cross Domain Conference for Machine Learning & Knowledge Extraction

CD-MAKE is a joint effort of IFIP TC 5, TC 12, IFIP WG 8.4, WG 8.9 and WG 12.9 and is held in conjunction with the International Conference on Availability, Reliability & Security, ARES 2020

Machine learning is the workhorse of Artificial Intelligence with enormous challenges in various application domains. It needs a concerted international effort without boundaries, supporting collaborative and integrative cross-disciplinary research between experts from diverse fields.

Conference Location: University College Dublin, Dublin, Ireland

Conference Website

EasyChair Submission Link:

Paper Submission Deadline: March 29,2020

Author Notification: May 14, 2020

Author Registration (latest): June, 14, 2020

Camera Ready (hard deadline!): June 19, 2020

Conference: August 25 – 28, 2020

The goal of the CD-MAKE conference is to act as an innovative catalysator and to bring together researchers from the following seven thematic sub-areas in a cross-disciplinary manner, to stimulate fresh ideas and to encourage multi-disciplinary problem solving:

- DATA - Data science (data fusion, preprocessing, mapping, knowledge representation, discovery)

- LEARNING - Machine learning algorithms, contextual adaptation, explainable-AI, causal reasoning

- VISUALIZATION - and visual analytics, intelligent user interfaces, human-computer interaction

- PRIVACY - data protection, safety, security, ethics, acceptance and social issues of ML

- NETWORK - graphical models, graph-based ML

- TOPOLOGY - geometrical machine learning, topological data analysis, manifold learning

- ENTROPY - time and machine learning, entropy-based ML

Each paper will be reviewed by at least three experts. Accepted Papers will appear in a Volume of Springer Lecture Notes in Computer Science (LNCS) and there is also the opportunity to publish in our MAKE Journal:

In line with CD-MAKE we organize the 2nd workshop on explainable AI (ex-AI):

Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
Disclaimer: ourGlocal is an open academical resource system, which anyone can edit or update. Usually, journal information updated by us, journal managers or others. So the information is old or wrong now. Specially, impact factor is changing every year. Even it was correct when updated, it may have been changed now. So please go to Thomson Reuters to confirm latest value about Journal impact factor.