mlsanityData to 14 Oct 2026

Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities

arXiv 2101.03655 ↗First posted 11 Jan 2021cs.LG cs.AIcited by 14

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Abstract (arXiv)

The emergence and continued reliance on the Internet and related technologies has resulted in the generation of large amounts of data that can be made available for analyses. However, humans do not possess the cognitive capabilities to understand such large amounts of data. Machine learning (ML) provides a mechanism for humans to process large amounts of data, gain insights about the behavior of the data, and make more informed decision based on the resulting analysis. ML has applications in various fields. This review focuses on some of the fields and applications such as education, healthcare, network security, banking and finance, and social media. Within these fields, there are multiple unique challenges that exist. However, ML can provide solutions to these challenges, as well as create further research opportunities. Accordingly, this work surveys some of the challenges facing the aforementioned fields and presents some of the previous literature works that tackled them. Moreover, it suggests several research opportunities that benefit from the use of ML to address these challenges.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 22 of its 161 references that are in the map. First posted on arXiv 11 Jan 2021.

Builds on

22 of 161 references.

References · 22

  1. 2016Federated Learning: Strategies for Improving Communication Efficiencycited by 1,475
  2. 2019Towards Federated Learning at Scale: System Designcited by 832
  3. 2018LEAF: A Benchmark for Federated Settingscited by 792
  4. 2019Federated Machine Learning: Concept and Applicationscited by 412
  5. 2016CNN-RNN: A Unified Framework for Multi-label Image Classificationcited by 190
  6. 2020On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practicecited by 182
  7. 2018A generic framework for privacy preserving deep learningcited by 103
  8. 2017End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Designcited by 88
  9. 2019Tree-based Intelligent Intrusion Detection System in Internet of Vehiclescited by 25
  10. 2020Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detectioncited by 17
  11. 2017On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Datasetcited by 11
  12. 2020Edge-enabled V2X Service Placement for Intelligent Transportation Systemscited by 11
10 more
  1. 2020Bayesian Optimization with Machine Learning Algorithms Towards Anomaly Detectioncited by 10
  2. 2020Detecting Botnet Attacks in IoT Environments: An Optimized Machine Learning Approachcited by 9
  3. 2020DNS Typo-squatting Domain Detection: A Data Analytics & Machine Learning Based Approachcited by 8
  4. 2020Ensemble-based Feature Selection and Classification Model for DNS Typo-squatting Detectioncited by 6
  5. 2020Multi-split Optimized Bagging Ensemble Model Selection for Multi-class Educational Data Miningcited by 5
  6. 2018Predicting drug response of tumors from integrated genomic profiles by deep neural networkscited by 4
  7. 2020Systematic Ensemble Model Selection Approach for Educational Data Miningcited by 4
  8. 2020Optimized Random Forest Model for Botnet Detection Based on DNS Queriescited by 3
  9. 2014The Predictive Power of Social Media: On the Predictability of U.S. Presidential Elections using Twittercited by 1
  10. 2020Relationship between Student Engagement and Performance in e-Learning Environment Using Association Rulescited by 1

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Cited by year

Citing papers per year: 2021: 4; 2022: 4; 2023: 2; 2024: 4.

14 papers.

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  1. 2023An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registrycited by 47
  2. 2021MTH-IDS: A Multi-Tiered Hybrid Intrusion Detection System for Internet of Vehiclescited by 36
  3. 2021PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streamscited by 17
  4. 2022IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning Perspectivecited by 16
  5. 2024On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Casecited by 9
  6. 2022LCCDE: A Decision-Based Ensemble Framework for Intrusion Detection in The Internet of Vehiclescited by 6
  7. 2021Machine Learning (ML)-Centric Resource Management in Cloud Computing: A Review and Future Directionscited by 4
  8. 2022Arabic Fake News Detection Based on Deep Contextualized Embedding Modelscited by 1
  9. 2023Ontology in Hybrid Intelligence: a concise literature reviewcited by 1
  10. 2024On the Intersection of Signal Processing and Machine Learning: A Use Case-Driven Analysis Approachcited by 1
  11. 2024The More the Merrier? Navigating Accuracy vs. Energy Efficiency Design Trade-Offs in Ensemble Learning Systemscited by 1
  12. 2021An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Datacited by 0
2 more
  1. 2022Anomaly Detection in Intra-Vehicle Networkscited by 0
  2. 2024Optimized Ensemble Model Towards Secured Industrial IoT Devicescited by 0