会議情報
MIX-AI 2018: MIX Summit and Conference on Artificial Intelligence and Machine Learning
https://www.mixsummit-ai.com
提出日:
2018-03-16
通知日:
2018-04-20
会議日:
2018-07-24
場所:
Dublin, Ireland
閲覧: 7428   追跡: 0   出席: 0

論文募集
MIX-AI will present some of the latest high-quality results and breakthroughs in Artificial Intelligence. The topics are framed to match the European Commission's Horizon 2020 societal challenges. It is planned that the results and papers presented at the conference will constitute a significant and holistic contribution to the growing knowledge based within the area of AI. To ensure this, the conference will consider and present research that is related to addressing the following areas:

1. AI for Health and Wellbeing
2. AI for Food/Agriculture & the Bioeconomy
3. AI for Energy & Environment
4. AI for Transportation
5. AI and its impact on Society
6. AI for Business & Finance

If your research is related to any of these topics, then we welcome a submission from you. Submissions can be from anywhere in the world and from any discipline.

MIX-AI uses EasyChair software for paper submissions. If you do not have an EasyChair account, then you will need to register one in order to submit. You can register and/or submit your paper by clicking the 'Submit Paper' button below.

Submission Information
​
Accepted Submissions Types 

    Full papers 

Papers in this category concern the traditional full papers of 12 pages. These should be aimed at presenting new and original work in Artificial Intelligence that meets the high-quality standards of MIX-AI. Mandatory abstract submissions of at most 200 words for the full papers are due by the deadline of 16th of March 2018; submissions of the final version of the entire full paper are due by the deadline of 11th of May 2018.

    Poster-only papers/Short Papers

Submissions are allowed that are targeted at being a poster-only paper of at most 2 pages, provided that if they are chosen for submission they are then extended to a short paper of at least 4 pages. Such papers should present work in Artificial Intelligence that is original, but has not yet reached the stage of the more mature, complete research results that are typically published in full papers at MIX-AI. Poster-only papers are due by the deadline of 16th of March 2018.

Both full and short papers must be done in accordance to the publisher's guidelines. Word templates that fit such guidelines can be downloaded here. 

Review Process

Each paper submitted to MIX-AI will be rigorously evaluated in a double-blind peer review process. Evaluation is done on a per-track basis, ensuring high interest and high expertise of the reviewers. Review criteria include the significance of the work, technical soundness, novelty, clarity, writing quality, relevance, and sufficiency of information to permit replication, if applicable.

Accepted papers will be given feedback on a TBC date, allowing authors to update their papers before full submission. 

Submission Terms

    Submit a final, revised, version to MIX-AI on or before the final deadline. 
    Register at least one author to attend the conference on or before the registration deadline
    Attend the conference (at least one author)
    Present the accepted paper at the conference

Anonymity 

Submitted papers should be anonymised. This means that they should NOT contain any element that may reveal the identity of their authors. This includes author names, affiliations, and acknowledgments. Moreover, any references to any of the author's own work should be made as if the work belonged to someone else.
最終更新 Dou Sun 2018-02-22
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完全な名前インパクト ・ ファクター出版社
SIGMOD Record ACM
Biomedical Signal Processing and Control4.900Elsevier
Computing and Informatics Institute of Informatics, Slovakia
World Wide Web2.700Springer
Human-centric Computing and Information SciencesSpringer
Journal of Web Semantics2.100Elsevier
Software Testing, Verification and Reliability1.500John Wiley & Sons, Ltd
Robotics and Computer-Integrated Manufacturing9.100Elsevier
ACM Transactions on Modeling and Performance Evaluation of Computing Systems0.700ACM
Security InformaticsSpringer
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