Machine Learning and Knowledge Extraction | Highly Cited and Hot Papers in 2022

We are pleased to invite you to read the highly cited and hot papers published in Machine Learning and Knowledge Extraction (MAKE, ISSN: 2504-4990) in 2022. We would like to take this opportunity to acknowledge the outstanding individuals and teams whose work inspires fellow researchers and profoundly influences all areas of machine learning and knowledge extraction. The list of papers is as follows:

1. “Machine Learning in Disaster Management: Recent Developments in Methods and Applications”
by Vasileios Linardos, Maria Drakaki, Panagiotis Tzionas and Yannis L. Karnavas
Mach. Learn. Knowl. Extr. 2022, 4(2), 446-473; https://doi.org/10.3390/make4020020
Available online: https://www.mdpi.com/2504-4990/4/2/20

2. “A Transfer Learning Evaluation of Deep Neural Networks for Image Classification”
by Nermeen Abou Baker, Nico Zengeler and Uwe Handmann
Mach. Learn. Knowl. Extr. 2022, 4(1), 22-41; https://doi.org/10.3390/make4010002
Available online: https://www.mdpi.com/2504-4990/4/1/2

3. “Hierarchical Reinforcement Learning: A Survey and Open Research Challenges”
by Matthias Hutsebaut-Buysse, Kevin Mets and Steven Latré
Mach. Learn. Knowl. Extr. 2022, 4(1), 172-221; https://doi.org/10.3390/make4010009
Available online: https://www.mdpi.com/2504-4990/4/1/9

4. “Machine Learning Based Restaurant Sales Forecasting”
by Austin Schmidt, Md Wasi Ul Kabir and Md Tamjidul Hoque
Mach. Learn. Knowl. Extr. 2022, 4(1), 105-130; https://doi.org/10.3390/make4010006
Available online: https://www.mdpi.com/2504-4990/4/1/6

5. “An Attention-Based ConvLSTM Autoencoder with Dynamic Thresholding for Unsupervised Anomaly Detection in Multivariate Time Series”
by Tareq Tayeh, Sulaiman Aburakhia, Ryan Myers and Abdallah Shami
Mach. Learn. Knowl. Extr. 2022, 4(2), 350-370; https://doi.org/10.3390/make4020015
Available online: https://www.mdpi.com/2504-4990/4/2/15

6. “Developing a Novel Fair-Loan Classifier through a Multi-Sensitive Debiasing Pipeline: DualFair”
by Arashdeep Singh, Jashandeep Singh, Ariba Khan and Amar Gupta
Mach. Learn. Knowl. Extr. 2022, 4(1), 240-253; https://doi.org/10.3390/make4010011
Available online: https://www.mdpi.com/2504-4990/4/1/11

7. “Robust Reinforcement Learning: A Review of Foundations and Recent Advances”
by Janosch Moos, Kay Hansel, Hany Abdulsamad, Svenja Stark, Debora Clever and Jan Peters
Mach. Learn. Knowl. Extr. 2022, 4(1), 276-315; https://doi.org/10.3390/make4010013
Available online: https://www.mdpi.com/2504-4990/4/1/13

8. “Explainable Machine Learning Reveals Capabilities, Redundancy, and Limitations of a Geospatial Air Quality Benchmark Dataset”
by Scarlet Stadtler, Clara Betancourt and Ribana Roscher
Mach. Learn. Knowl. Extr. 2022, 4(1), 150-171; https://doi.org/10.3390/make4010008
Available online: https://www.mdpi.com/2504-4990/4/1/8

9. “Fairness and Explanation in AI-Informed Decision Making”
by Alessa Angerschmid, Jianlong Zhou, Kevin Theuermann, Fang Chen and Andreas Holzinger
Mach. Learn. Knowl. Extr. 2022, 4(2), 556-579; https://doi.org/10.3390/make4020026
Available online: https://www.mdpi.com/2504-4990/4/2/26

10. “Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication”
by Nyle Siddiqui, Rushit Dave, Mounika Vanamala and Naeem Seliya
Mach. Learn. Knowl. Extr. 2022, 4(2), 502-518; https://doi.org/10.3390/make4020023
Available online: https://www.mdpi.com/2504-4990/4/2/23