CFP: IEEE IJCNN/WCCI 2024 - Special Session on Multi-Objective Automated Machine Learning [DEADLINE: January 15]

[Mustafa MISIR]

** Apologies for cross-posting **

Call for Papers

Special Session on  MO-AutoML: Multi-Objective Automated Machine Learning @ IEEE WCCI /  IJCNN 2024

For more details: https://sites.google.com/view/moautoml/

The International Joint Conference on Neural Networks (IJCNN 2024)
The IEEE World Congress on Computational Intelligence (IEEE WCCI 2024)

Yokohama, Japan; June 30 - July 5, 2024

Submission deadline:  January 15, 2024

For submission: https://2024.ieeewcci.org/ijcnn-call-for-papers 


Scope: With the aim of automatically locating machine learning configurations and design choices with the best performance possible in constrained resources and without human involvement, Automated Machine Learning (AutoML) views the Machine Learning (ML) task as a search and optimization problem. This approach reduces the machine's reliance on human experts by enabling automation in data preparation, feature engineering, model generation, and model estimation. ML applications in the real world naturally have more than one objective. Prediction measures, model complexity, training time, and power consumption are some example objectives. Thus, when designing an AutoML system, considering multiple objectives is critical.

The aim of this special session is to gather researchers studying Multi-Objective AutoML to share their research on the following non-exhaustive list of topics:

- Multi-objective Automated Neural Architecture Search (NAS)
- Multi-objective Automated Hyper-parameter Optimization / Tuning (HPO)
- Multi-objective Automated Feature Engineering
- Multi-objective Automated Data Augmentation
- Multi-objective Automated Data Cleaning
- Multi-objective Automated Model Compression
- Multi-objective Automated Model Combination
- Multi-Objective AutoML tools, frameworks, and benchmarks

Organizers:

- Zhongyi Hu, Wuhan University, China,  zhong...@whu.edu.cn
- Mustafa Misir, Duke Kunshan University, China,  mustaf...@dukekunshan.edu.cn
- Yi Mei, Victoria University of Wellington, New Zealand,  yi....@ecs.vuw.ac.nz

Special session website: https://sites.google.com/view/moautoml/

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Best regards,

 

Mustafa MISIR

 

Assoc. Prof. of Data and Computational Science

Lead, Machine lEarning and Operations Research (MEmORy) Lab

Division of Natural and Applied Sciences

Duke Kunshan University

Duke Avenue No. 8, Kunshan, Jiangsu, China 215316  

 

Web: http://mustafamisir.github.io  |  http://memoryrlab.github.io