The 27th International Conference on Neural Information Processing
(ICONIP2020)

Special Session:

Human-in-the-Loop Interactions in Machine Learning

Bangkok, Thailand
18-22 Nov 2020

ICONIP2020-Special Session:

Human-in-the-Loop Interactions in Machine Learning

Brief Description

Extracting information from a massive amount of humans’ natural behaviour and cognition patterns has allowed supporting the machine learning and decisions in many fields, ranging from computer science to engineering. Human-in-the-loop approaches interact with machine learning are gaining popularity as a better approach to training more accurate models, because the human feedback into the learning loop of the machine can help it improve faster. Recent advances in machine learning, are giving momentum to human-in- the-loop approaches to enable complex paradigms that operate in connection with human beings.

 

Given the remarkable achievement associated with the processing of human physiological signals obtained from neuroimaging modalities and cognitive systems, it has been proposed as a useful and effective framework for the modelling and understanding of human behaviour and cognition patterns as well as to enable a direct communication pathway between the human and machine. This paves the way for developing new human-in-the- loop interacting and interfacing techniques in reasoning and machine learning that foster the capabilities for understanding and modelling the training process.

This special session is aimed at gathering outstanding papers about integrating human informatics and their interacting applications using machine learning. This will provide a snapshot of the latest advances in the contribution of human-in-the-loop interactions powered by reasoning or learning frameworks.

Scope and Topics:

The list of possible topics includes, but is not limited to:
o Neural modelling and reasoning for the recognition of human cognitive processes. 

o Neurocomputing models for decoding of brain activity patterns and brain-computer/machine interactions and interfaces.
o Human-centred computing approach to support human data analytics and neuro-informatics.
o Neural networks for the acquisition of human uncertainties and vulnerabilities.
o Theoretical development of human-in-the-loop learning.
o Applications of neural processing techniques and machine learning in human datasets.

 
 

Dr. Zehong (Jimmy) Cao,

University of Tasmania, TAS, Australia

Email: Zehong.Cao@utas.edu.au

 

Prof. Chin-Teng Lin,

University of Technology Sydney, NSW, Australia

Email:Chin- Teng.Lin@uts.edu.au

 

​Prof. Dongrui Wu,

Huazhong University of Science and Technology, Wuhan, China

Email: drwu@hust.edu.cn

 

Submission Guideline

Important Dates:

  • Paper submission: June 1, 2020 (extended)

  • Paper notification: August 15, 2020

  • Camera-ready deadline: September 15, 2020

 

Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of ICONIP 2020.

 

Authors who submit papers to this session are invited to select “Special Session - Human-in-the-Loop Interactions in Machine Learning”. Submissions to regular and special sessions follow identical format, instructions, deadlines and procedures of the other papers.

 

For further information and news, please refer to the ICONIP 2020 website: https://www.apnns.org/ICONIP2020/

RSVP for our specail session. See you soon!
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