Ricardo B. C. Prudêncio

According to our database1, Ricardo B. C. Prudêncio authored at least 92 papers between 2002 and 2019.

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

Timeline

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Bibliography

2019
Empirical investigation of active learning strategies.
Neurocomputing, 2019

CD-CARS: Cross-domain context-aware recommender systems.
Expert Syst. Appl., 2019

β3-IRT: A New Item Response Model and its Applications.
CoRR, 2019

Item response theory in AI: Analysing machine learning classifiers at the instance level.
Artif. Intell., 2019

A Multivariate Method for Group Profiling Using Subgroup Discovery.
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

$β^3$-IRT: A New Item Response Model and its Applications.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Centrality-Based Group Profiling: A Comparative Study in Co-authorship Networks.
New Generation Comput., 2018

Data complexity meta-features for regression problems.
Machine Learning, 2018

AVS: An approach to identifying and mitigating duplicate bug reports.
Proceedings of the XIV Brazilian Symposium on Information Systems, 2018

Transferring Knowledge From Texts to Images by Combining Deep Semantic Feature Descriptors.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Increasing Convolutional Neural Networks Training Speed by Incremental Complexity Learning.
Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

Ensemble Methods for Label Noise Detection Under the Noisy at Random Model.
Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

Instance Selection and Class Balancing Techniques for Cross Project Defect Prediction.
Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017
H3AD: A hybrid hyper-heuristic for algorithm design.
Inf. Sci., 2017

Generation of Particle Swarm Optimization algorithms: An experimental study using Grammar-Guided Genetic Programming.
Appl. Soft Comput., 2017

Unsupervised Aspect Term Extraction in Online Drugs Reviews.
Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Aspect-Based Opinion Mining in Drug Reviews.
Proceedings of the Progress in Artificial Intelligence, 2017

2016
A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data.
Neural Networks, 2016

Active learning and data manipulation techniques for generating training examples in meta-learning.
Neurocomputing, 2016

Progress in intelligent systems design.
Neurocomputing, 2016

A multiple kernel learning algorithm for drug-target interaction prediction.
BMC Bioinformatics, 2016

Reframing in context: A systematic approach for model reuse in machine learning.
AI Commun., 2016

Making Sense of Item Response Theory in Machine Learning.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

A Novel Context-Free Grammar to Guide the Construction of Particle Swarm Optimization Algorithms.
Proceedings of the 5th Brazilian Conference on Intelligent Systems, 2016

Tree-Based Grammar Genetic Programming to Evolve Particle Swarm Algorithms.
Proceedings of the 5th Brazilian Conference on Intelligent Systems, 2016

A Comparative Study of Group Profiling Techniques in Co-authorship Networks.
Proceedings of the 5th Brazilian Conference on Intelligent Systems, 2016

2015
A hybrid particle swarm optimization and harmony search algorithm approach for multi-objective test case selection.
J. Braz. Comp. Soc., 2015

A literature review of recommender systems in the television domain.
Expert Syst. Appl., 2015

Versatile Decision Trees for Learning Over Multiple Contexts.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

GEFPSO: A Framework for PSO Optimization based on Grammatical Evolution.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

I/S-Race: An iterative Multi-Objective Racing Algorithm for the SVM Parameter Selection Problem.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Context-Aware Techniques for Cross-Domain Recommender Systems.
Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015

Semi-supervised Multi-label k-Nearest Neighbors Classification Algorithms.
Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015

2014
A hybrid meta-learning architecture for multi-objective optimization of SVM parameters.
Neurocomputing, 2014

A collaborative filtering framework based on local and global similarities with similarity tie-breaking criteria.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Fine-tuning of support vector machine parameters using racing algorithms.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Similarity Measures of Algorithm Performance for Cost-Sensitive Scenarios.
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

A comparison study of binary multi-objective Particle Swarm Optimization approaches for test case selection.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

A Hybrid Binary Multi-objective Particle Swarm Optimization with Local Search for Test Case Selection.
Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

Cost-Sensitive Measures of Algorithm Similarity for Meta-learning.
Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

2013
Search based constrained test case selection using execution effort.
Expert Syst. Appl., 2013

Proximity measures for link prediction based on temporal events.
Expert Syst. Appl., 2013

Group Profiling for Understanding Educational Social Networking.
Proceedings of the 25th International Conference on Software Engineering and Knowledge Engineering, 2013

Active selection of training instances for a random forest meta-learner.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Active testing for SVM parameter selection.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012
Combining Uncertainty Sampling methods for supporting the generation of meta-examples.
Inf. Sci., 2012

Combining meta-learning and search techniques to select parameters for support vector machines.
Neurocomputing, 2012

Leveraging relationships in social networks for sentiment analysis.
Proceedings of the Brazilian Symposium on Multimedia and the Web, 2012

Using link structure to infer opinions in social networks.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2012

Combining a multi-objective optimization approach with meta-learning for SVM parameter selection.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2012

Combining Meta-Learning with Multi-objective Particle Swarm Algorithms for SVM Parameter Selection: An Experimental Analysis.
Proceedings of the 2012 Brazilian Symposium on Neural Networks, 2012

Time Series Based Link Prediction.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Multi-objective optimization and Meta-learning for SVM parameter selection.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Collective Classification for Sentiment Analysis in Social Networks.
Proceedings of the IEEE 24th International Conference on Tools with Artificial Intelligence, 2012

An Experimental Study of the Combination of Meta-Learning with Particle Swarm Algorithms for SVM Parameter Selection.
Proceedings of the Computational Science and Its Applications - ICCSA 2012, 2012

2011
Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach.
Proceedings of the Meta-Learning in Computational Intelligence, 2011

Feature and algorithm selection with Hybrid Intelligent Techniques.
Int. J. Hybrid Intell. Syst., 2011

Supervised link prediction in weighted networks.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Uncertainty sampling methods for selecting datasets in active meta-learning.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

A Multi-objective Particle Swarm Optimization for Test Case Selection Based on Functional Requirements Coverage and Execution Effort.
Proceedings of the IEEE 23rd International Conference on Tools with Artificial Intelligence, 2011

Good to be Bad? Distinguishing between Positive and Negative Citations in Scientific Impact.
Proceedings of the IEEE 23rd International Conference on Tools with Artificial Intelligence, 2011

Uncertainty Sampling-Based Active Selection of Datasetoids for Meta-learning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Combining Meta-learning and Active Selection of Datasetoids for Algorithm Selection.
Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

2010
Randomized constraint solvers: a comparative study.
ISSE, 2010

A Constrained Particle Swarm Optimization Approach for Test Case Selection.
Proceedings of the 22nd International Conference on Software Engineering & Knowledge Engineering (SEKE'2010), Redwood City, San Francisco Bay, CA, USA, July 1, 2010

Local Feature Selection for Generation of Ensembles in Text Clustering.
Proceedings of the 11th Brazilian Symposium on Neural Networks (SBRN 2010), 2010

Combining Meta-learning and Search Techniques to SVM Parameter Selection.
Proceedings of the 11th Brazilian Symposium on Neural Networks (SBRN 2010), 2010

2009
Combining Text Classifiers and Hidden Markov Models for Information Extraction.
International Journal on Artificial Intelligence Tools, 2009

A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing.
Proceedings of the First NASA Formal Methods Symposium, 2009

Combining Uncertainty Sampling Methods for Active Meta-Learning.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

Active Generation of Training Examples in Meta-Regression.
Proceedings of the Artificial Neural Networks, 2009

Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data.
Proceedings of the Artificial Neural Networks, 2009

2008
Selective generation of training examples in active meta-learning.
Int. J. Hybrid Intell. Syst., 2008

Selecting Neural Network Forecasting Models Using the Zoomed-Ranking Approach.
Proceedings of the 10th Brazilian Symposium on Neural Networks (SBRN 2008), 2008

Using Support Vector Machines to Predict the Performance of MLP Neural Networks.
Proceedings of the 10th Brazilian Symposium on Neural Networks (SBRN 2008), 2008

Automatic Information Extraction in Semi-structured Official Journals.
Proceedings of the 10th Brazilian Symposium on Neural Networks (SBRN 2008), 2008

Ranking and selecting clustering algorithms using a meta-learning approach.
Proceedings of the International Joint Conference on Neural Networks, 2008

Active Meta-Learning with Uncertainty Sampling and Outlier Detection.
Proceedings of the International Joint Conference on Neural Networks, 2008

Local Feature Selection in Text Clustering.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Predicting the Performance of Learning Algorithms Using Support Vector Machines as Meta-regressors.
Proceedings of the Artificial Neural Networks, 2008

Hidden Markov Models and Text Classifiers for Information Extraction on Semi-Structured Texts.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

2007
Active Learning to Support the Generation of Meta-examples.
Proceedings of the Artificial Neural Networks, 2007

Active Selection of Training Examples for Meta-Learning.
Proceedings of the 7th International Conference on Hybrid Intelligent Systems (HIS 2007), 2007

2006
LearningWeights for Linear Combination of Forecasting Methods.
Proceedings of the SBRN 2006, 2006

A Machine Learning Approach to Define Weights for Linear Combination of Forecasts.
Proceedings of the Artificial Neural Networks, 2006

A Hybrid Machine Learning Approach for Information Extraction.
Proceedings of the 6th International Conference on Hybrid Intelligent Systems (HIS 2006), 2006

2004
A Modal Symbolic Classifier for selecting time series models.
Pattern Recognit. Lett., 2004

Meta-learning approaches to selecting time series models.
Neurocomputing, 2004

Selection of Time Series Forecasting Models based on Performance Information.
Proceedings of the 4th International Conference on Hybrid Intelligent Systems (HIS 2004), 2004

Using Machine Learning Techniques to Combine Forecasting Methods.
Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

2003
Selecting and Ranking Time Series Models Using the NOEMON Approach.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

2002
Selection of Models for Time Series Prediction via Meta-Learning.
Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002


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