Selection of Models for Time Series Prediction via Meta-Learning. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (HIS, 2002)

Selecting and Ranking Time Series Models Using the NOEMON Approach. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (ICANN, 2003)

Using Machine Learning Techniques to Combine Forecasting Methods. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (Australian Conference on Artificial Intelligence, 2004)

Selection of Time Series Forecasting Models based on Performance Information. - Patrícia Maforte dos Santos; Teresa Bernarda Ludermir; Ricardo Bastos Cavalcante Prudêncio (HIS, 2004)

Meta-learning approaches to selecting time series models. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (Neurocomputing, 2004)

A Modal Symbolic Classifier for selecting time series models. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir; Francisco de A. T. de Carvalho (Pattern Recognit. Lett., 2004)

A Hybrid Machine Learning Approach for Information Extraction. - Eduardo F. A. Silva; Flávia A. Barros; Ricardo Bastos Cavalcante Prudêncio (HIS, 2006)

A Machine Learning Approach to Define Weights for Linear Combination of Forecasts. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (ICANN (1), 2006)

LearningWeights for Linear Combination of Forecasting Methods. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (SBRN, 2006)

Active Selection of Training Examples for Meta-Learning. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (HIS, 2007)

Active Learning to Support the Generation of Meta-examples. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (ICANN (1), 2007)

Hidden Markov Models and Text Classifiers for Information Extraction on Semi-Structured Texts. - Flávia A. Barros; Eduardo F. A. Silva; Ricardo Bastos Cavalcante Prudêncio; Valmir M. Filho; André C. A. Nascimento (HIS, 2008)

Predicting the Performance of Learning Algorithms Using Support Vector Machines as Meta-regressors. - Silvio B. Guerra; Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (ICANN (1), 2008)

Local Feature Selection in Text Clustering. - Marcelo Nunes Ribeiro; Manoel J. R. Neto; Ricardo Bastos Cavalcante Prudêncio (ICONIP (2), 2008)

Active Meta-Learning with Uncertainty Sampling and Outlier Detection. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (IJCNN, 2008)

Ranking and selecting clustering algorithms using a meta-learning approach. - Marcílio Carlos Pereira de Souto; Ricardo Bastos Cavalcante Prudêncio; Rodrigo G. F. Soares; Daniel S. A. de Araujo; Ivan G. Costa; Teresa Bernarda Ludermir; Alexander Schliep (IJCNN, 2008)

Automatic Information Extraction in Semi-structured Official Journals. - Valmir Macário Filho; Ricardo Bastos Cavalcante Prudêncio; Francisco de A. T. de Carvalho; Leandro R. Torres; Laerte Rodrigues Jr.; Marcos G. Lima (SBRN, 2008)

Using Support Vector Machines to Predict the Performance of MLP Neural Networks. - Ricardo Bastos Cavalcante Prudêncio; Silvio B. Guerra; Teresa Bernarda Ludermir (SBRN, 2008)

Selecting Neural Network Forecasting Models Using the Zoomed-Ranking Approach. - Patrícia M. Santos; Teresa Bernarda Ludermir; Ricardo Bastos Cavalcante Prudêncio (SBRN, 2008)

Selective generation of training examples in active meta-learning. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (Int. J. Hybrid Intell. Syst., 2008)

Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data. - André C. A. Nascimento; Ricardo Bastos Cavalcante Prudêncio; Marcílio Carlos Pereira de Souto; Ivan G. Costa (ICANN (2), 2009)

Active Generation of Training Examples in Meta-Regression. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (ICANN (1), 2009)

Combining Uncertainty Sampling Methods for Active Meta-Learning. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (ISDA, 2009)

A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing. - Mitsuo Takaki; Diego Cavalcanti; Rohit Gheyi; Juliano Iyoda; Marcelo d'Amorim; Ricardo Bastos Cavalcante Prudêncio (NASA Formal Methods, 2009)

Combining Text Classifiers and Hidden Markov Models for Information Extraction. - Flávia A. Barros; Eduardo F. A. Silva; Ricardo Bastos Cavalcante Prudêncio; Valmir M. Filho; André C. A. Nascimento (Int. J. Artif. Intell. Tools, 2009)

Combining Meta-learning and Search Techniques to SVM Parameter Selection. - Taciana A. F. Gomes; Ricardo Bastos Cavalcante Prudêncio; Carlos Soares; André L. D. Rossi; André Carlos Ponce de Leon Ferreira de Carvalho (SBRN, 2010)

Local Feature Selection for Generation of Ensembles in Text Clustering. - Marcelo Nunes Ribeiro; Ricardo Bastos Cavalcante Prudêncio (SBRN, 2010)

A Constrained Particle Swarm Optimization Approach for Test Case Selection. - Luciano S. de Souza; Ricardo Bastos Cavalcante Prudêncio; Flávia de Almeida Barros (SEKE, 2010)

Randomized constraint solvers: a comparative study. - Mitsuo Takaki; Diego Cavalcanti; Rohit Gheyi; Juliano Iyoda; Marcelo d'Amorim; Ricardo Bastos Cavalcante Prudêncio (Innov. Syst. Softw. Eng., 2010)

Combining Meta-learning and Active Selection of Datasetoids for Algorithm Selection. - Ricardo Bastos Cavalcante Prudêncio; Carlos Soares; Teresa Bernarda Ludermir (HAIS (1), 2011)

Uncertainty Sampling-Based Active Selection of Datasetoids for Meta-learning. - Ricardo Bastos Cavalcante Prudêncio; Carlos Soares; Teresa Bernarda Ludermir (ICANN (2), 2011)

Good to be Bad? Distinguishing between Positive and Negative Citations in Scientific Impact. - Diana C. Cavalcanti; Ricardo Bastos Cavalcante Prudêncio; Shreyasee S. Pradhan; Jatin Shah; Ricardo Pietrobon (ICTAI, 2011)

A Multi-objective Particle Swarm Optimization for Test Case Selection Based on Functional Requirements Coverage and Execution Effort. - Luciano S. de Souza; Péricles Barbosa C. de Miranda; Ricardo Bastos Cavalcante Prudêncio; Flávia de Almeida Barros (ICTAI, 2011)

Uncertainty sampling methods for selecting datasets in active meta-learning. - Ricardo Bastos Cavalcante Prudêncio; Carlos Soares; Teresa Bernarda Ludermir (IJCNN, 2011)

Supervised link prediction in weighted networks. - Hially Rodrigues de Sa; Ricardo Bastos Cavalcante Prudêncio (IJCNN, 2011)

Feature and algorithm selection with Hybrid Intelligent Techniques. - Teresa Bernarda Ludermir; Ricardo Bastos Cavalcante Prudêncio; Cleber Zanchettin (Int. J. Hybrid Intell. Syst., 2011)

Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach. - Ricardo Bastos Cavalcante Prudêncio; Marcilio C. P. de Souto; Teresa Bernarda Ludermir (Meta-Learning in Computational Intelligence, 2011)

An Experimental Study of the Combination of Meta-Learning with Particle Swarm Algorithms for SVM Parameter Selection. - Péricles Barbosa C. de Miranda; Ricardo Bastos Cavalcante Prudêncio; André Carlos Ponce de Leon Ferreira de Carvalho; Carlos Soares (ICCSA (3), 2012)

Collective Classification for Sentiment Analysis in Social Networks. - Juliano C. B. Rabelo; Ricardo B. C. Prudêncio; Flávia A. Barros (ICTAI, 2012)

Multi-objective optimization and Meta-learning for SVM parameter selection. - Péricles B. C. Miranda; Ricardo Bastos Cavalcante Prudêncio; André Carlos Ponce de Leon Ferreira de Carvalho; Carlos Soares (IJCNN, 2012)

Time Series Based Link Prediction. - Paulo Ricardo da Silva Soares; Ricardo Bastos Cavalcante Prudêncio (IJCNN, 2012)

Combining Meta-Learning with Multi-objective Particle Swarm Algorithms for SVM Parameter Selection: An Experimental Analysis. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio; André C. P. L. F. de Carvalho; Carlos Soares (SBRN, 2012)

Combining a multi-objective optimization approach with meta-learning for SVM parameter selection. - Péricles Barbosa C. de Miranda; Ricardo Bastos Cavalcante Prudêncio; André Carlos Ponce de Leon Ferreira de Carvalho; Carlos Soares (SMC, 2012)

Using link structure to infer opinions in social networks. - Juliano C. B. Rabelo; Ricardo B. C. Prudêncio; Flávia de Almeida Barros (SMC, 2012)

Leveraging relationships in social networks for sentiment analysis. - Juliano C. B. Rabelo; Ricardo B. C. Prudêncio; Flávia A. Barros (WebMedia, 2012)

Combining meta-learning and search techniques to select parameters for support vector machines. - Taciana A. F. Gomes; Ricardo Bastos Cavalcante Prudêncio; Carlos Soares; André L. D. Rossi; André C. P. L. F. de Carvalho (Neurocomputing, 2012)

Combining Uncertainty Sampling methods for supporting the generation of meta-examples. - Ricardo Bastos Cavalcante Prudêncio; Teresa Bernarda Ludermir (Inf. Sci., 2012)

Active testing for SVM parameter selection. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio (IJCNN, 2013)

Active selection of training instances for a random forest meta-learner. - Arthur F. M. Sousa; Ricardo B. C. Prudêncio; Carlos Soares; Teresa Bernarda Ludermir (IJCNN, 2013)

Group Profiling for Understanding Educational Social Networking. - João Gomes; Ricardo B. C. Prudêncio; Luciano Meira; Alexandre Azevedo Filho; André C. A. Nascimento; Hilário Oliveira (SEKE, 2013)

Proximity measures for link prediction based on temporal events. - Paulo Ricardo da Silva Soares; Ricardo B. C. Prudêncio (Expert Syst. Appl., 2013)

Search based constrained test case selection using execution effort. - Luciano S. de Souza; Ricardo B. C. Prudêncio; Flávia de Almeida Barros; Eduardo Henrique da Silva Aranha (Expert Syst. Appl., 2013)

Cost-Sensitive Measures of Algorithm Similarity for Meta-learning. - Carlos Eduardo Castor de Melo; Ricardo Bastos Cavalcante Prudêncio (BRACIS, 2014)

A Hybrid Binary Multi-objective Particle Swarm Optimization with Local Search for Test Case Selection. - Luciano S. de Souza; Ricardo B. C. Prudêncio; Flávia de Almeida Barros (BRACIS, 2014)

A comparison study of binary multi-objective Particle Swarm Optimization approaches for test case selection. - Luciano S. de Souza; Ricardo B. C. Prudêncio; Flávia de Almeida Barros (IEEE Congress on Evolutionary Computation, 2014)

Similarity Measures of Algorithm Performance for Cost-Sensitive Scenarios. - Carlos Eduardo Castor de Melo; Ricardo B. C. Prudêncio (MetaSel@ECAI, 2014)

Fine-tuning of support vector machine parameters using racing algorithms. - Péricles B. C. Miranda; Paulo Ricardo da Silva Soares; Ricardo B. C. Prudêncio (ESANN, 2014)

A collaborative filtering framework based on local and global similarities with similarity tie-breaking criteria. - Andre R. S. Lopes; Ricardo B. C. Prudêncio; Byron L. D. Bezerra (IJCNN, 2014)

A hybrid meta-learning architecture for multi-objective optimization of SVM parameters. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio; André C. P. L. F. de Carvalho; Carlos Soares (Neurocomputing, 2014)

Semi-supervised Multi-label k-Nearest Neighbors Classification Algorithms. - Danilo C. G. de Lucena; Ricardo B. C. Prudêncio (BRACIS, 2015)

Context-Aware Techniques for Cross-Domain Recommender Systems. - Douglas Veras da Silva; Ricardo B. C. Prudêncio; Carlos Ferraz; Alysson Bispo; Thiago Monteiro Prota (BRACIS, 2015)

I/S-Race: An iterative Multi-Objective Racing Algorithm for the SVM Parameter Selection Problem. - Péricles Barbosa C. de Miranda; Paulo Ricardo da Silva Soares; Ricardo B. C. Prudêncio (ESANN, 2015)

GEFPSO: A Framework for PSO Optimization based on Grammatical Evolution. - Péricles Barbosa C. de Miranda; Ricardo Bastos Cavalcante Prudêncio (GECCO, 2015)

Versatile Decision Trees for Learning Over Multiple Contexts. - Reem Al-Otaibi; Ricardo B. C. Prudêncio; Meelis Kull; Peter A. Flach (ECML/PKDD (1), 2015)

A literature review of recommender systems in the television domain. - Douglas Veras da Silva; Thiago Monteiro Prota; Alysson Bispo; Ricardo B. C. Prudêncio; Carlos Ferraz (Expert Syst. Appl., 2015)

A hybrid particle swarm optimization and harmony search algorithm approach for multi-objective test case selection. - Luciano S. de Souza; Ricardo Bastos Cavalcante Prudêncio; Flávia A. Barros (J. Braz. Comput. Soc., 2015)

A Comparative Study of Group Profiling Techniques in Co-authorship Networks. - João Emanoel Ambrósio Gomes; Ricardo B. C. Prudêncio; André C. A. Nascimento (BRACIS, 2016)

Tree-Based Grammar Genetic Programming to Evolve Particle Swarm Algorithms. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio (BRACIS, 2016)

A Novel Context-Free Grammar to Guide the Construction of Particle Swarm Optimization Algorithms. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio (BRACIS, 2016)

Making Sense of Item Response Theory in Machine Learning. - Fernando Martínez-Plumed; Ricardo B. C. Prudêncio; Adolfo Martínez Usó; José Hernández-Orallo (ECAI, 2016)

Reframing in context: A systematic approach for model reuse in machine learning. - José Hernández-Orallo; Adolfo Martínez Usó; Ricardo B. C. Prudêncio; Meelis Kull; Peter A. Flach; Chowdhury Farhan Ahmed; Nicolas Lachiche (AI Commun., 2016)

A multiple kernel learning algorithm for drug-target interaction prediction. - André C. A. Nascimento; Ricardo B. C. Prudêncio; Ivan G. Costa (BMC Bioinform., 2016)

Progress in intelligent systems design. - Ricardo B. C. Prudêncio; Teresa Bernarda Ludermir (Neurocomputing, 2016)

Active learning and data manipulation techniques for generating training examples in meta-learning. - Arthur F. M. Sousa; Ricardo B. C. Prudêncio; Teresa Bernarda Ludermir; Carlos Soares (Neurocomputing, 2016)

A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data. - Telmo de Menezes e Silva Filho; Renata M. C. R. Souza; Ricardo B. C. Prudêncio (Neural Networks, 2016)

Aspect-Based Opinion Mining in Drug Reviews. - Diana C. Cavalcanti; Ricardo B. C. Prudêncio (EPIA, 2017)

Unsupervised Aspect Term Extraction in Online Drugs Reviews. - Diana C. Cavalcanti; Ricardo B. C. Prudêncio (FLAIRS, 2017)

Generation of Particle Swarm Optimization algorithms: An experimental study using Grammar-Guided Genetic Programming. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio (Appl. Soft Comput., 2017)

H3AD: A hybrid hyper-heuristic for algorithm design. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio; Gisele L. Pappa (Inf. Sci., 2017)

Instance Selection and Class Balancing Techniques for Cross Project Defect Prediction. - Alysson Bispo; Ricardo B. C. Prudêncio; Douglas Veras da Silva (BRACIS, 2018)

Ensemble Methods for Label Noise Detection Under the Noisy at Random Model. - Kecia Gomes de Moura; Ricardo Bastos Cavalcante Prudêncio; George Darmiton da Cunha Cavalcanti (BRACIS, 2018)

Increasing Convolutional Neural Networks Training Speed by Incremental Complexity Learning. - Miguel Domingos de Santana Wanderley; Ricardo Bastos Cavalcante Prudêncio (BRACIS, 2018)

Transferring Knowledge From Texts to Images by Combining Deep Semantic Feature Descriptors. - Miguel D. de S. Wanderley; Ricardo B. C. Prudêncio (IJCNN, 2018)

AVS: An approach to identifying and mitigating duplicate bug reports. - Ivan Santos; Joelson Araújo; Cloves Lima; Ricardo B. C. Prudêncio; Flávia A. Barros (SBSI, 2018)

Data complexity meta-features for regression problems. - Ana Carolina Lorena; Aron I. Maciel; Péricles Barbosa C. de Miranda; Ivan G. Costa; Ricardo B. C. Prudêncio (Mach. Learn., 2018)

Centrality-Based Group Profiling: A Comparative Study in Co-authorship Networks. - João Emanoel Ambrósio Gomes; Ricardo B. C. Prudêncio; André C. A. Nascimento (New Gener. Comput., 2018)

$β^3$-IRT: A New Item Response Model and its Applications. - Yu Chen; Telmo de Menezes e Silva Filho; Ricardo B. C. Prudêncio; Tom Diethe; Peter A. Flach (AISTATS, 2019)

A Multivariate Method for Group Profiling Using Subgroup Discovery. - Tarcísio Lucas; João Gomes; Renato Vimieiro; Ricardo B. C. Prudêncio; Teresa Bernarda Ludermir (BRACIS, 2019)

Cost Sensitive Evaluation of Instance Hardness in Machine Learning. - Ricardo B. C. Prudêncio (ECML/PKDD (2), 2019)

Item response theory in AI: Analysing machine learning classifiers at the instance level. - Fernando Martínez-Plumed; Ricardo B. C. Prudêncio; Adolfo Martínez Usó; José Hernández-Orallo (Artif. Intell., 2019)

β3-IRT: A New Item Response Model and its Applications. - Yu Chen; Telmo de Menezes e Silva Filho; Ricardo B. C. Prudêncio; Tom Diethe; Peter A. Flach (CoRR, 2019)

CD-CARS: Cross-domain context-aware recommender systems. - Douglas Veras da Silva; Ricardo B. C. Prudêncio; Carlos Ferraz (Expert Syst. Appl., 2019)

Empirical investigation of active learning strategies. - Davi Pereira dos Santos; Ricardo Bastos Cavalcante Prudêncio; André Carlos Ponce de Leon Ferreira de Carvalho (Neurocomputing, 2019)

Measuring Instance Hardness Using Data Complexity Measures. - José L. M. Arruda; Ricardo B. C. Prudêncio; Ana Carolina Lorena (BRACIS (2), 2020)

Decoding Machine Learning Benchmarks. - Lucas F. F. Cardoso; Vitor C. A. Santos; Regiane S. K. Francês; Ricardo B. C. Prudêncio; Ronnie C. O. Alves (BRACIS (2), 2020)

A Many-Objective optimization Approach for Complexity-based Data set Generation. - Thiago R. Fraça; Péricles B. C. Miranda; Ricardo B. C. Prudêncio; Ana C. Lorenaz; André C. A. Nascimento (CEC, 2020)

Item Response Theory to Estimate the Latent Ability of Speech Synthesizers. - Chaina Santos Oliveira; Caio C. A. Tenório; Ricardo B. C. Prudêncio (ECAI, 2020)

Item Response Theory for Evaluating Regression Algorithms. - João V. C. Moraes; Jessica T. S. Reinaldo; Ricardo B. C. Prudêncio; Telmo de Menezes e Silva Filho (IJCNN, 2020)

One-Class Classification for Selecting Synthetic Datasets in Meta-Learning. - Regina R. Parente; Ricardo B. C. Prudêncio (IJCNN, 2020)

A novel context-free grammar for the generation of PSO algorithms. - Péricles B. C. Miranda; Ricardo B. C. Prudêncio (Nat. Comput., 2020)

A Process for Building Domain Specific Thesauri for Query Expansion to Mine SW Documents Repositories within an Industrial Environment. - Mailton Carvalho; Flávia A. Barros; Ricardo B. C. Prudêncio (SBES, 2021)

Data vs classifiers, who wins? - Lucas F. F. Cardoso; Vitor C. A. Santos; Regiane S. Kawasaki Francês; Ricardo B. C. Prudêncio; Ronnie C. O. Alves (CoRR, 2021)

Meta-aprendizado para otimizacao de parametros de redes neurais. - Tarsicio Lucas; Teresa Bernarda Ludermir; Ricardo B. C. Prudêncio; Carlos Soares (CoRR, 2021)

ImageDataset2Vec: An image dataset embedding for algorithm selection. - Lucas V. Dias; Péricles B. C. Miranda; André C. A. Nascimento; Filipe R. Cordeiro; Rafael Ferreira Mello; Ricardo B. C. Prudêncio (Expert Syst. Appl., 2021)

Explanation-by-Example Based on Item Response Theory. - Lucas F. F. Cardoso; José de S. Ribeiro; Vitor Cirilo Araujo Santos; Raíssa Lorena Silva da Silva; Marcelle Pereira Mota; Ricardo B. C. Prudêncio; Ronnie C. O. Alves (BRACIS (1), 2022)

Explaining Learning Performance with Local Performance Regions and Maximally Relevant Meta-Rules. - Ricardo B. C. Prudêncio; Telmo de Menezes e Silva Filho (BRACIS (1), 2022)

Predicting Compatibility of Cultivars in Grafting Processes Using Kernel Methods and Collaborative Filtering. - Thiago B. R. Silva; Nina I. Verslype; André C. A. Nascimento; Ricardo B. C. Prudêncio (BRACIS (1), 2022)

Item Response Theory to Evaluate Speech Synthesis: Beyond Synthetic Speech Difficulty. - Chaina Santos Oliveira; Ricardo B. C. Prudêncio (EBeM@IJCAI, 2022)

A Clustering-Based Method to Anomaly Detection in Thermal Power Plants. - Patrícia Drapal; Jullya Clemente; Dailys Maite Aliaga Reyes; Starch Melo de Souza; Anthony Lins; Ricardo B. C. Prudêncio (IJCNN, 2022)

Label noise detection under the noise at random model with ensemble filters. - Kecia Gomes de Moura; Ricardo B. C. Prudêncio; George D. C. Cavalcanti (Intell. Data Anal., 2022)

Evaluating regression algorithms at the instance level using item response theory. - João V. C. Moraes; Jessica T. S. Reinaldo; Manuel Ferreira Junior; Telmo de Menezes e Silva Filho; Ricardo B. C. Prudêncio (Knowl. Based Syst., 2022)

A two-level Item Response Theory model to evaluate speech synthesis and recognition. - Chaina Santos Oliveira; João V. C. Moraes; Telmo de Menezes e Silva Filho; Ricardo B. C. Prudêncio (Speech Commun., 2022)

Assessor Models with a Reject Option for Soccer Result Prediction. - Daniel C. Da Costa; Ricardo B. C. Prudêncio; Alexandre Mota 001 (ICMLA, 2023)

Machine Learning Techniques for Escaped Defect Analysis in Software Testing. - Lidia Perside Gomes Nascimento; Ricardo Bastos Cavalcante Prudêncio; Alexandre Cabral Mota; Audir de Araujo Paiva Filho; Pedro Henrique Alves Cruz; Daniel Cardoso Coelho Alves de Oliveira; Pedro Roncoli Sarmet Moreira (SAST, 2023)

β4-IRT: A New β3-IRT with Enhanced Discrimination Estimation. - Manuel Ferreira Junior; Jessica T. S. Reinaldo; Telmo de Menezes e Silva Filho; Eufrasio A. Lima Neto; Ricardo B. C. Prudêncio (CoRR, 2023)

Meta-Learning and Novelty Detection for Machine Learning with Reject Option. - Patrícia Drapal; Telmo de Menezes e Silva Filho; Ricardo B. C. Prudêncio (IJCNN, 2024)

Measuring Latent Traits of Instance Hardness and Classifier Ability using Boltzmann Machines. - Eduardo Vargas Ferreira; Ricardo Bastos Cavalcante Prudêncio; Ana Carolina Lorena (IJCNN, 2024)

Low-Pass Filter Application for Anomaly Detection with Sparse Autoencoder. - Maira Farias Andrade Lira; Elias Amancio Siqueira-Filho; Ricardo B. C. Prudêncio (IJCNN, 2024)

Assessor Models for Explaining Instance Hardness in Classification Problems. - Ricardo B. C. Prudêncio; Ana Carolina Lorena; Telmo de Menezes e Silva Filho; Patrícia Drapal; Maria Gabriela Valeriano (IJCNN, 2024)

Towards explainable evaluation: Explaining predicted performance using local performance regions. - Patrícia Drapal; Ricardo B. C. Prudêncio; Telmo de Menezes e Silva Filho (Appl. Soft Comput., 2024)

Trusting My Predictions: On the Value of Instance-Level Analysis. - Ana Carolina Lorena; Pedro Yuri Arbs Paiva; Ricardo B. C. Prudêncio (ACM Comput. Surv., 2024)

Enhancing Classifier Evaluation: A Fairer Benchmarking Strategy Based on Ability and Robustness. - Lucas F. F. Cardoso; Vitor C. A. Santos; José de S. Ribeiro; Regiane Kawasaki; Ricardo B. C. Prudêncio; Ronnie Alves (CoRR, 2025)

An item response theory framework to evaluate automatic speech recognition systems against speech difficulty. - Chaina Santos Oliveira; Ricardo B. C. Prudêncio (Comput. Speech Lang., 2026)