Information
Starts: 02.02.2021 08:00
Ends: 04.02.2021 18:00
Location:
Sanya, China
Sanya
China
Promoter
NameMs. Maggie Lau
Telephone13880104517
Email[email protected]
Websiteiccda.org
Description

The International Conference on Compute 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 compute 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. ICCDA 2021 conference will be located in Sanya, China during February 2-4, 2021.

 

*Proceedings:

Accepted and presented papers will be published into the ACM Proceedings (ISBN: 978-1-4503-8911-2), indexed by Ei compendex, scopus, etc.

 

*Venue:

Harman Resort Hotel Sanya (pending)

136 Yuya Road, Jiyang District, 572000 Sanya, China

 

*Keynote Speakers:

Lili Qiu, The University of Texas at Austin, USA (ACM Fellow, IEEE Fellow, and ACM Distinguished Scientist);

Hai Jin, Huazhong University of Science and Technology, China (IEEE Fellow, CCF Fellow);

Zhiguo Gong, The University of Macau.

 

*Invited Speakers:

Yucong Duan, Hainan University, China;

Lei Li, Hefei University of Technology, China.

 

*Previous ICCDA:

Past ICCDA papers were all published in the prestigious ACM proceedings:

ICCDA 2020, ISBN: 978-1-4503-7644-0, EI, Scopus indexing

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:

http://www.easychair.org/conferences/?conf=iccda2021

 

*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

 

*Contact:

Ms. Maggie Lau

[email protected]

Wechat: iconf-cs

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