Miguel Guimarães

Orcid: 0000-0003-0573-9122

According to our database1, Miguel Guimarães authored at least 14 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Block size, parallelism and predictive performance: finding the sweet spot in distributed learning.
Int. J. Parallel Emergent Distributed Syst., May, 2024

2023
A multiple criteria approach for building a pandemic impact assessment composite indicator: The case of COVID-19 in Portugal.
Eur. J. Oper. Res., September, 2023

Algorithm Recommendation and Performance Prediction Using Meta-Learning.
Int. J. Neural Syst., March, 2023

Using meta-learning to predict performance metrics in machine learning problems.
Expert Syst. J. Knowl. Eng., 2023

The Impact of Data Selection Strategies on Distributed Model Performance.
Proceedings of the Ambient Intelligence - Software and Applications, 2023

2022
A predictive and user-centric approach to Machine Learning in data streaming scenarios.
Neurocomputing, 2022

Continuously Learning from User Feedback.
Proceedings of the Information Systems and Technologies, 2022

Real-Time Algorithm Recommendation Using Meta-Learning.
Proceedings of the Ambient Intelligence - Software and Applications, 2022

Explainable Decision Tree on Smart Human Mobility.
Proceedings of the Workshops at 18th International Conference on Intelligent Environments (IE2022), 2022

2021
A multiple criteria approach for constructing a pandemic impact assessment composite indicator: The case of Covid-19 in Portugal.
CoRR, 2021

Optimizing Model Training in Interactive Learning Scenarios.
Proceedings of the Trends and Applications in Information Systems and Technologies, 2021

A Conversational Interface for interacting with Machine Learning models.
Proceedings of 4th International Workshop on eXplainable and Responsible AI and Law co-located with 18th International Conference on Artificial Intelligence and Law (ICAIL 2021), 2021

2020
Explainable Intelligent Environments.
Proceedings of the Ambient Intelligence - Software and Applications, 2020

Optimizing Instance Selection Strategies in Interactive Machine Learning: An Application to Fraud Detection.
Proceedings of the Hybrid Intelligent Systems, 2020


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