Optimized Learning Vector Quantization Classifier with an Adaptive Euclidean Distance. - Renata M. C. R. de Souza; Telmo de Menezes e Silva Filho (ICANN (1), 2009)

Pattern classifiers with adaptive distances. - Telmo de Menezes e Silva Filho; Renata M. C. R. de Souza (IJCNN, 2011)

A Weighted Learning Vector Quantization Approach for Interval Data. - Telmo de Menezes e Silva Filho; Renata Maria Cardoso R. de Souza (ICONIP (3), 2012)

Fuzzy learning vector quantization approaches for interval data. - Telmo de Menezes e Silva Filho; Renata M. C. R. Souza (FUZZ-IEEE, 2013)

Hybrid methods for fuzzy clustering based on fuzzy c-means and improved particle swarm optimization. - Telmo de Menezes e Silva Filho; Bruno A. Pimentel; Renata M. C. R. Souza; Adriano L. I. Oliveira (Expert Syst. Appl., 2015)

Background Check: A General Technique to Build More Reliable and Versatile Classifiers. - Miquel Perelló-Nieto; Telmo de Menezes e Silva Filho; Meelis Kull; Peter A. Flach (ICDM, 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)

Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers. - Meelis Kull; Telmo de Menezes e Silva Filho; Peter A. Flach (AISTATS, 2017)

A parametrized approach for linear regression of interval data. - Leandro Carlos de Souza; Renata M. C. R. Souza; Getúlio J. A. Amaral; Telmo de Menezes e Silva Filho (Knowl. Based Syst., 2017)

An interval prototype classifier based on a parameterized distance applied to breast thermographic images. - Marcus C. Araújo; Renata M. C. R. Souza; Rita C. F. Lima; Telmo de Menezes e Silva Filho (Medical Biol. Eng. Comput., 2017)

$β^3$-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)

Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration. - Meelis Kull; Miquel Perelló-Nieto; Markus Kängsepp; Telmo de Menezes e Silva Filho; Hao Song 007; Peter A. Flach (NeurIPS, 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)

Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration. - Meelis Kull; Miquel Perelló-Nieto; Markus Kängsepp; Telmo de Menezes e Silva Filho; Hao Song 007; Peter A. Flach (CoRR, 2019)

Investigating different fitness criteria for swarm-based clustering. - Maria Priscila Da Silva Souza; Telmo de Menezes e Silva Filho; Getúlio José Amorim do Amaral; Renata Maria Cardoso Rodrigues De Souza (Int. J. Bus. Intell. Data Min., 2019)

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)

Automatic Segmentation of Mammary Tissue using Computer Simulations of Breast Phantoms and Deep-learning Techniques. - Lucca R. Peregrino; Jordy V. Gomes; Thaís Gaudencio do Rêgo; Yuri de A. M. Barbosa; Telmo de Menezes e Silva Filho; Andrew D. A. Maidment; Bruno Barufaldi (BIOSIGNALS, 2021)

Iris-CV: Classifying Iris Flowers Is Not as Easy as You Thought. - Itamar Rocha Filho; João Pedro Vasconcelos Teixeira; João Wallace Lucena Lins; Felipe Honorato de Sousa; Ana Clara Chaves Sousa; Manuel Ferreira Junior; Thaís Ramos; Cecília Silva; Thaís Gaudencio do Rêgo; Yuri de Almeida Malheiros; Telmo de Menezes e Silva Filho (BRACIS (2), 2021)

A Comparative Study on Concept Drift Detectors for Regression. - Marília Lima; Telmo de Menezes e Silva Filho; Roberta Fagundes (BRACIS (1), 2021)

Classifier Calibration: How to assess and improve predicted class probabilities: a survey. - Telmo de Menezes e Silva Filho; Hao Song 007; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Meelis Kull; Peter A. Flach (CoRR, 2021)

Kohonen map-wise regression applied to interval data. - Leandro Carlos de Souza; Bruno A. Pimentel; Telmo de Menezes e Silva Filho; Renata M. C. R. de Souza (Knowl. Based Syst., 2021)

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)

Automatic Recognition of Units of Measurement in Product Descriptions from Tax Invoices Using Neural Networks. - Lucas Fernandes Lucena; Telmo de Menezes e Silva Filho; Thaís Gaudencio do Rêgo; Yuri Malheiros (PROPOR, 2022)

Evaluating Data Representations for Object Recognition During Pick-and-Place Manipulation Tasks. - Humberto Navarro de Carvalho; Lucas Pontes Castro; Thaís Gaudencio do Rêgo; Telmo de Menezes e Silva Filho; Yuri de A. M. Barbosa; Leonardo Vidal Batista; Amílcar Soares 001; Vinicius Prado da Fonseca (SysCon, 2022)

Learning Under Concept Drift for Regression - A Systematic Literature Review. - Marília Lima; Manoel Alves de Almeida Neto; Telmo de Menezes e Silva Filho; Roberta A. de A. Fagundes (IEEE Access, 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)

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)

Hierarchical GNNs for Large Graph Generation. - Alex O. Davies; Nirav S. Ajmeri; Telmo de Menezes e Silva Filho (CoRR, 2023)

Its All Graph To Me: Foundational Topology Models with Contrastive Learning on Multiple Domains. - Alex O. Davies; Riku W. Green; Nirav S. Ajmeri; Telmo de Menezes e Silva Filho (CoRR, 2023)

Classifier calibration: a survey on how to assess and improve predicted class probabilities. - Telmo de Menezes e Silva Filho; Hao Song 007; Miquel Perelló-Nieto; Raúl Santos-Rodríguez; Meelis Kull; Peter A. Flach (Mach. Learn., 2023)

Classifying breast lesions in Brazilian thermographic images using convolutional neural networks. - Flávia R. S. Brasileiro; Delmiro D. Sampaio Neto; Telmo de Menezes e Silva Filho; Renata M. C. R. de Souza; Marcus C. de Araújo (Neural Comput. Appl., 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)

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)

Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting. - Riku Green; Grant Stevens; Telmo de Menezes e Silva Filho; Zahraa S. Abdallah (CoRR, 2024)

Stratify: Unifying Multi-Step Forecasting Strategies. - Riku Green; Grant Stevens; Zahraa Said Abdallah; Telmo de Menezes e Silva Filho (CoRR, 2024)

Assessment of volumetric dense tissue segmentation in tomosynthesis using deep virtual clinical trials. - Bruno Barufaldi; Jordy V. Gomes; Telmo de Menezes e Silva Filho; Thaís Gaudencio do Rêgo; Yuri Malheiros; Trevor Lewis Vent; Aimilia Gastounioti; Andrew D. A. Maidment (Pattern Recognit., 2024)

Sighted particles: improving swarm optimization by making particles aware of their surroundings. - Wagner J. F. Silva; Telmo de Menezes e Silva Filho; Delmiro D. Sampaio Neto; Renata M. C. R. Souza; Adriano L. I. Oliveira; Francisco José de A. Cysneiros (Evol. Intell., 2024)

Recommendation systems with user and item profiles based on symbolic modal data. - Delmiro D. Sampaio Neto; Telmo de Menezes e Silva Filho; Renata M. C. R. Souza (Neural Comput. Appl., 2024)

A Comparative Study of GNNs and Rule-Based Methods for Synthetic Social Network Generation. - Alex O. Davies; Nirav S. Ajmeri; Telmo de Menezes e Silva Filho (IEEE Access, 2025)

Investigations into deep Reinforcement Learning for wind farm set-point optimisation. - Helen Sheehan; Daniel J. Poole; Telmo de Menezes e Silva Filho; Ervin Bossanyi; Lars Landberg (Expert Syst. Appl., 2025)

A Metric for the Balance of Information in Graph Learning. - Alex O. Davies; Nirav S. Ajmeri; Telmo de Menezes e Silva Filho (CoRR, 2025)