Luís Paulo F. Garcia

Orcid: 0000-0003-0679-9143

Affiliations:
  • University of Sao Paulo, Brazil


According to our database1, Luís Paulo F. Garcia authored at least 32 papers between 2009 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

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Bibliography

2024
A review on preprocessing algorithm selection with meta-learning.
Knowl. Inf. Syst., January, 2024

2023
Neural architecture search with interpretable meta-features and fast predictors.
Inf. Sci., November, 2023

Applying One-Class Algorithms for Data Stream-Based Insider Threat Detection.
IEEE Access, 2023

Model Performance Prediction: A Meta-Learning Approach for Concept Drift Detection.
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023

Financial Distress Prediction in an Imbalanced Data Stream Environment.
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023

2022
Meta-features for meta-learning.
Knowl. Based Syst., 2022

2021
Assessing the data complexity of imbalanced datasets.
Inf. Sci., 2021

Towards holistic Entity Linking: Survey and directions.
Inf. Syst., 2021

An Anomaly-based Multi-class Classifier for Network Intrusion Detection.
CoRR, 2021

A Study of the Correlation of Metafeatures Used for Metalearning.
Proceedings of the Advances in Computational Intelligence, 2021

Evaluating Clustering Meta-features for Classifier Recommendation.
Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

2020
MFE: Towards reproducible meta-feature extraction.
J. Mach. Learn. Res., 2020

Boosting meta-learning with simulated data complexity measures.
Intell. Data Anal., 2020

Algorithm Recommendation for Data Streams.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

OPTIC: A Deep Neural Network Approach for Entity Linking using Word and Knowledge Embeddings.
Proceedings of the 22nd International Conference on Enterprise Information Systems, 2020

Simulating Complexity Measures on Imbalanced Datasets.
Proceedings of the Intelligent Systems - 9th Brazilian Conference, 2020

2019
New label noise injection methods for the evaluation of noise filters.
Knowl. Based Syst., 2019

How Complex Is Your Classification Problem?: A Survey on Measuring Classification Complexity.
ACM Comput. Surv., 2019

The Influence of Sampling on Imbalanced Data Classification.
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2018
Towards Reproducible Empirical Research in Meta-Learning.
CoRR, 2018

Data Complexity Measures for Imbalanced Classification Tasks.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Classifier Recommendation Using Data Complexity Measures.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017
The NoiseFiltersR Package: Label Noise Preprocessing in R.
R J., 2017

2016
Detecção de ruídos em problemas de classificação.
PhD thesis, 2016

Noise detection in the meta-learning level.
Neurocomputing, 2016

Ensembles of label noise filters: a ranking approach.
Data Min. Knowl. Discov., 2016

2015
Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems.
Knowl. Based Syst., 2015

Effect of label noise in the complexity of classification problems.
Neurocomputing, 2015

Adapting Noise Filters for Ranking.
Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015

2013
Noisy Data Set Identification.
Proceedings of the Hybrid Artificial Intelligent Systems - 8th International Conference, 2013

2012
A Study on Class Noise Detection and Elimination.
Proceedings of the 2012 Brazilian Symposium on Neural Networks, 2012

2009
Use of Classification Algorithms in Noise Detection and Elimination.
Proceedings of the Hybrid Artificial Intelligence Systems, 4th International Conference, 2009


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