2020 The 3rd International Conference on Machine Learning and Machine Intelligence (MLMI 2020)

Conference / Summit (onsite)
Artificial Intelligence (AI) & Machine Learning (ML); Computer Science

Address: Hangzhou, Hangzhou, China
Date: 18 to 20 Sep '20

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Welcome to 2020 The 3rd International Conference on Machine Learning and Machine Intelligence (MLMI 2020) that will be held in Hangzhou, China during  September 18-20, 2020.

Insightful presentations, engaging discussions, vibrant networking – MLMI 2020 has it all. With leading academics on the scientific committee of the event, the program is guaranteed to address the most relevant topics in the field of machine learning and machine intelligence. It's an opportunity to source feedback on your research, to get published in conference proceedings, and to explore the beautiful city Hangzhou, China.

We invite you to join us for three days of learning and networking. You are guaranteed to leave the event with a suitcase full of knowledge and inspiration.

Publication:
Accepted papers of MLMI 2020 after registration and presentation will be published in the MLMI 2020 Conference Proceedings, which will be submitted for indexing by Ei Compendex, Scopus, etc.

Conference Chairs:
  • Prof. Dapeng Wu, IEEE Fellow, University of Florida, USA
  • Prof. Jianjun Li, Hangzhou Dianzi University, China

Program Chairs:
  • Prof. James Tin-Yau Kwok, IEEE Fellow, Hong Kong University of Science and Technology, Hong Kong
  • Prof. Jianhua Zhang, Oslo Metropolitan University, Norway

Publicity Chair:
  • Prof. Xiaolin Qin, University of Chinese Academy of Sciences, China

Steering Committee:
  • Prof. Jianhua Dai, Hunan Normal University, China

Contact:
☞ Conference Secretary: Ms. Yolanda Dong
☏ Tel: +86-18080013977
✉ Email: mlmi@iacsit.net  

Topics of interest for submission include, but are not limited to:

  • Artificial Neural Networks 
  • Association Rule Learning  
  • Automata, Logic and Games  
  • Bayesian Networks  
  • Clustering 
  • Commercial Software
  • Commercial Software with Open-Source Editions  
  • Complex Systems 
  • Computational Complexity  
  • Computational Learning Theory  
  •  Computational Linguistics  
  •  Computer Animation
  • Computer Science 
  • Computer System 
  • Concurrent Algorithms and Data Structures  
  • Data Mining  
  • Decision Tree Learning  
  • Deep Learning
  • Genetic Algorithms
  • Inductive Logic Programming
  • Intelligent Systems
  • Lambda Calculus and Types
  • Logic and Proof
  • Machine Learning
  • Models of Computation
  • Object-Oriented Programming
  • Open-Source Software
  • Pattern Recognition
  • Reinforcement Learning
  • Representation Learning
  • Similarity and Metric Learning
  • Sparse Dictionary Learning
  • Supervised Learning
  • Support Vector Machines
  • Unsupervised Learning

Important Update about COVID-19: Online Presentation

We fully understand that some participants cannot attend the conference in person due to COVID-19. In this case, you could choose online presentation.

Moreover, in order to provide a safer conference environment, the organizer will actively take some actions, such as, encourage every participant wear the mask during the conference, take every participant's temperature before they enter, etc.

We would like to thank for your support to the conference despite the current crisis situation. Please contact mlmi@iacsit.net for more information about online presentation.

Topics of interest for submission include, but are not limited to:

  • Artificial Neural Networks 
  • Association Rule Learning  
  • Automata, Logic and Games  
  • Bayesian Networks  
  • Clustering 
  • Commercial Software
  • Commercial Software with Open-Source Editions  
  • Complex Systems 
  • Computational Complexity  
  • Computational Learning Theory  
  •  Computational Linguistics  
  •  Computer Animation
  • Computer Science 
  • Computer System 
  • Concurrent Algorithms and Data Structures  
  • Data Mining  
  • Decision Tree Learning  
  • Deep Learning
  • Genetic Algorithms
  • Inductive Logic Programming
  • Intelligent Systems
  • Lambda Calculus and Types
  • Logic and Proof
  • Machine Learning
  • Models of Computation
  • Object-Oriented Programming
  • Open-Source Software
  • Pattern Recognition
  • Reinforcement Learning
  • Representation Learning
  • Similarity and Metric Learning
  • Sparse Dictionary Learning
  • Supervised Learning
  • Support Vector Machines
  • Unsupervised Learning

Important Update about COVID-19: Online Presentation

We fully understand that some participants cannot attend the conference in person due to COVID-19. In this case, you could choose online presentation.

Moreover, in order to provide a safer conference environment, the organizer will actively take some actions, such as, encourage every participant wear the mask during the conference, take every participant's temperature before they enter, etc.

We would like to thank for your support to the conference despite the current crisis situation. Please contact mlmi@iacsit.net for more information about online presentation.

Prof. Dapeng Wu

IEEE Fellow
University of Florida, USA
Keynote Speaker

Prof. Huan Liu

IEEE Fellow & ACM Fellow
Arizona State University, USA
Keynote Speaker

Prof. James T. Kwok

IEEE Fellow
Hong Kong University of Science and Technology, Hong Kong
Keynote Speaker

IConf

Media Partner

Prof. Dapeng Wu

IEEE Fellow
University of Florida, USA
Keynote Speaker

Prof. Huan Liu

IEEE Fellow & ACM Fellow
Arizona State University, USA
Keynote Speaker

Prof. James T. Kwok

IEEE Fellow
Hong Kong University of Science and Technology, Hong Kong
Keynote Speaker

IConf

Media Partner

Venue

Hangzhou

Organizer

International Association of Computer Science & Information Technology

Venue

Hangzhou

Organizer

International Association of Computer Science & Information Technology

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