Sponsor: info@iimt.ac.in IIMT Bhubaneswar

2ndInternational Conference on Applied Machine Learning (ICAML-2020)

(Date 16th - 18th October 2020 )
Organised by: Hunan University of Finance and Economics. Place: Changsha, China.

Publication Paper Submission Register

About (ICAML-2020)

Due to the COVID-19, 2nd International Conference on Applied Machine Learning (ICAML-2020) shall be organized by Hunan University of Finance and Economics with “offline + online” sync mode and will be held during October 16-18, 2020 in Changsha, China.

Machine learning is a multidisciplinary subject that includes field of computer science, artificial intelligence, statistics and operation research etc. The objective of machine learning is to understand the structure of data and fit that data into models that can be understood and utilized by people. Machine Learning facilitates computers in building models from sample data in order to automate decision-making processes based on data inputs. Currently Machine Learning techniques are very much useful in research work to improve efficiency, speed and accuracy of outcomes in the presence of large-scale data. The continuous development of machine learning tools and techniques is responsible for understanding the non-linearity existing in the data, extracting several features, finding hidden patterns in data, classifying data into labels and so on. This has led to the tremendous advancement and spread in applications ranging from personalized product recommendations to speech recognition in cell phones; from predictive analytics to security applications that leverage machine learning for implementing filters and safe guards against new threats; from data mining programs that discover general rules in large data sets, to information filtering systems that automatically learn users' interests. It also innovatively powers various application sectors such as manufacturing, retail, healthcare, finance, travel, hospitality, science and engineering etc.

The goal

The goal of ICAML is to provide a broad platform to the key areas in machine learning along with emphasizing various application sectors. It aims to bring together researchers, practitioners and scholars from both academia and industry to share their knowledge, exchange ideas and establish new collaborations.

The following topics arebeing included, but not limited to:
Artificial Intelligence, Deep Learning, Cognitive Computing, Image Analysis, Text Analytics, Speech Recognition, Natural Language Processing, Cyber and Cloud Security, Industry 4.0, Internet of Things, Manufacturing and retail Sector: Operational Issues & Challenges, Financial Analytics, Revenue Management, Health Sector Services, Marketing Operations & Efficiency Measures, Public Systems operations management, Systems Studies, Coastal-zone Management: best practices & operational issues, Applications of Mathematical & Statistical Models, Power generation and grids, Smart buildings and cities, Industrial optimization, Agriculture, forestry and other land use, Disaster management and relief, Ecosystems and natural resources, Extreme weather events, Data and voice communication, etc.

Contact

FOR INTERNATIONAL AUTHORS:

QQ: 3603521247
Wechat: 17680151052
Email: ICAML2020@163.com

FOR INDIAN AUTHORS:

Miss. Lopamudra Behera
Interscience Institute of Management and Technology,
Bhubaneswar, India

Ph: 7809092085

Email: coordinator.conference@iimt.ac.in

For Authors

Authors are encouraged to contribute to the conference by submitting original research papers illustrating their research works, industrial projects, state-of-the-art reviews on applied machine learning and its significant advances

Important Dates

Conference Calender

 

Submission of papers: 15th August 2020
Notification of acceptance: 25th September 2020
Camera-ready papers: 1st October 2020
Registration & payment: 10th October 2020
Conference date:
16th AND 18th OCTOBER 2020

Venue

Address

Jasmine International Hotel Changsha,
No.528, Mid Jinxing Road, Yuelu District, Changsha

State

China,

Contact No

+86-17680146683

Mail Id

398006989@qq.com

knowledge management