2023 The 7th International Conference on Computing and Data Analysis (ICCDA 2023)

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2023 The 7th International Conference on Computing and Data Analysis (ICCDA 2023)

Website: http://iccda.org/

Place

Guiyang, China

Conference Date

Sep 15 - Sep 17, 2023

Submission Deadline

Aug 10, 2023

Venue

Guizhou University

Subjects: Computer Science and Technologies

Sponsorship: 

Indexing: EI Compendex,Scopus

Short Description

Full name: 2023 The 7th International Conference on Computing and Data Analysis
Abbreviation: ICCDA 2023
September 15-17, 2023 - Guiyang, China
More details, please visit: http://iccda.org/
 
The International Conference on Computing and Data Analysis (ICCDA), is an annual conference hold each year. It is an international forum for academia and industries to exchange visions and ideas in the state of the art and practice of computing and data analysis.
 
The previous editions of ICCDA were held in Florida Polytechnic University, Lakeland, Northern Illinois University (NIU) DeKalb, University of Hawaii Maui College, Kahului, Silicon Valley, USA, Sanya, China (Virtual); Shanghai, China (Virtual). ICCDA 2023 conference will be located in Guiyang, China during September 15-17, 2023.
 
*Proceedings:
Full Paper submitted and accepted after successful registration will be published by ACM Conference Proceedings (ISBN: 979-8-4007-0057-6) , the content will be submitted to Ei compendex, Scopus, etc.
 
*Previous ICCDA:
Past ICCDA papers were all published in the prestigious ACM proceedings:
ICCDA 2022, ISBN: 978-1-4503-9547-2, EI, Scopus indexed
ICCDA 2021, ISBN: 978-1-4503-8911-2, EI, Scopus indexed
ICCDA 2020, ISBN: 978-1-4503-7644-0, EI, Scopus indexed
ICCDA 2019, ISBN: 978-1-4503-6634-2, EI, Scopus indexed
ICCDA 2018, ISBN: 978-1-4503-6359-4, EI, Scopus indexed
ICCDA 2017, ISBN: 978-1-4503-5241-3, EI, Scopus indexed
 
*Submission Link:
https://www.zmeeting.org/submission/iccda2023
 
*Topics:
Mathematical, probabilistic and statistical models and theories
Machine learning theories, models and systems
Knowledge discovery theories, models and systems
Manifold and metric learning
Deep learning
Scalable analysis and learning
Non-iidness learning
Heterogeneous data/information integration
Data pre-processing, sampling and reduction
Dimensionality reduction
Feature selection, transformation and construction
Large scale optimization
High performance computing for data analytics
Architecture, management and process for data science
More topics: http://iccda.org/cfp.html
 
*Venue:
Guizhou University 
Address: South Jiaxiu Road, Huaxi District, Guiyang, Guizhou, China
 
*Contact:
Ms. Maggie X. Xu
Tel.: +86 180 8007 5398
Email: iccda_info@163.com
Wechat: iconf-cs-1

Contact

E-mail: iccda_info@163.com

Tel: 

Rank: ★★★★

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