Elden, L (2007). Matrix Methods in Data Mining and Pattern Recognition. Philadelphia (USA): Society for Industrial and Applied Mathematics. - Stefan Wermter; Renato Cordeiro de Amorim (Cogn. Syst. Res., 2009)

Computational Methods of Feature Selection, Huan Liu, Hiroshi Motoda, CRC Press, Boca Raton, FL (2007), 440 pp, ISBN 978-1-58488-878-9 - Renato Cordeiro de Amorim (Inf. Process. Manag., 2009)

Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire: Successes and New Directions in Data Mining. - Renato Cordeiro de Amorim (Inf. Retr., 2009)

An Adaptive Spell Checker Based on PS3M: Improving the Clusters of Replacement Words. - Renato Cordeiro de Amorim (Computer Recognition Systems 3, 2009)

Weighting Features for Partition around Medoids Using the Minkowski Metric. - Renato Cordeiro de Amorim; Trevor I. Fenner (IDA, 2012)

On Initializations for the Minkowski Weighted K-Means. - Renato Cordeiro de Amorim; Peter Komisarczuk (IDA, 2012)

An Empirical Evaluation of Different Initializations on the Number of K-Means Iterations. - Renato Cordeiro de Amorim (MICAI (1), 2012)

Anomalous pattern based clustering of mental tasks with subject independent learning - some preliminary results. - Renato Cordeiro de Amorim; Boris G. Mirkin; John Q. Gan (Artif. Intell. Res., 2012)

Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering. - Renato Cordeiro de Amorim; Boris G. Mirkin (Pattern Recognit., 2012)

A Clustering-Based Approach to Reduce Feature Redundancy. - Renato Cordeiro de Amorim; Boris G. Mirkin (KICSS, 2013)

Effective Spell Checking Methods Using Clustering Algorithms. - Renato Cordeiro de Amorim; Marcos Zampieri (RANLP, 2013)

Partitional Clustering of Malware Using K-Means. - Renato Cordeiro de Amorim; Peter Komisarczuk (Cyberpatterns, 2014)

Challenges in developing Capture-HPC exclusion lists. - Mohammad Puttaroo; Peter Komisarczuk; Renato Cordeiro de Amorim (SIN, 2014)

Between Sound and Spelling: Combining Phonetics and Clustering Algorithms to Improve Target Word Recovery. - Marcos Zampieri; Renato Cordeiro de Amorim (PolTAL, 2014)

Feature Relevance in Ward's Hierarchical Clustering Using the L p Norm. - Renato Cordeiro de Amorim (J. Classif., 2015)

Recovering the number of clusters in data sets with noise features using feature rescaling factors. - Renato Cordeiro de Amorim; Christian Hennig (Inf. Sci., 2015)

A Survey on Feature Weighting Based K-Means Algorithms. - Renato Cordeiro de Amorim (J. Classif., 2016)

Applying subclustering and Lp distance in Weighted K-Means with distributed centroids. - Renato Cordeiro de Amorim; Vladimir Makarenkov (Neurocomputing, 2016)

A-Wardpβ: Effective hierarchical clustering using the Minkowski metric and a fast k-means initialisation. - Renato Cordeiro de Amorim; Vladimir Makarenkov; Boris G. Mirkin (Inf. Sci., 2016)

The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning. - Renato Cordeiro de Amorim; Andrei Shestakov; Boris G. Mirkin; Vladimir Makarenkov (Pattern Recognit., 2017)

An efficient density-based clustering algorithm using reverse nearest neighbour. - Stiphen Chowdhury; Renato Cordeiro de Amorim (CoRR, 2018)

Feature weighting as a tool for unsupervised feature selection. - Deepak Panday; Renato Cordeiro de Amorim; Peter C. R. Lane (Inf. Process. Lett., 2018)

Unsupervised feature selection for large data sets. - Renato Cordeiro de Amorim (Pattern Recognit. Lett., 2019)

Core Clustering as a Tool for Tackling Noise in Cluster Labels. - Renato Cordeiro de Amorim; Vladimir Makarenkov; Boris G. Mirkin (J. Classif., 2020)

Unified Transformer Multi-Task Learning for Intent Classification With Entity Recognition. - Alberto José Benayas Álamos; Reyhaneh Hashempour; Damian Rumble; Shoaib Jameel; Renato Cordeiro de Amorim (IEEE Access, 2021)

Improving cluster recovery with feature rescaling factors. - Renato Cordeiro de Amorim; Vladimir Makarenkov (Appl. Intell., 2021)

Identifying meaningful clusters in malware data. - Renato Cordeiro de Amorim; Carlos David Lopez Ruiz (Expert Syst. Appl., 2021)

An Extensive Empirical Comparison of k-means Initialization Algorithms. - Simon Harris; Renato Cordeiro de Amorim (IEEE Access, 2022)

Feature weighting in DBSCAN using reverse nearest neighbours. - Stiphen Chowdhury; Na Helian; Renato Cordeiro de Amorim (Pattern Recognit., 2023)

On Sum-Free Subsets of Abelian Groups. - Renato Cordeiro de Amorim (Axioms, 2023)

On k-means iterations and Gaussian clusters. - Renato Cordeiro de Amorim; Vladimir Makarenkov (Neurocomputing, 2023)

Inertia-Based Indices to Determine the Number of Clusters in K-Means: An Experimental Evaluation. - Andrei Rykov; Renato Cordeiro de Amorim; Vladimir Makarenkov; Boris G. Mirkin (IEEE Access, 2024)

A Deep Learning Approach to Language-independent Gender Prediction on Twitter. - Reyhaneh Hashempour; Barbara Plank; Aline Villavicencio; Renato Cordeiro de Amorim (CoRR, 2024)

Improving clustering quality evaluation in noisy Gaussian mixtures. - Renato Cordeiro de Amorim; Vladimir Makarenkov (CoRR, 2025)

Scalable unsupervised feature selection via weight stability. - Xudong Zhang; Renato Cordeiro de Amorim (CoRR, 2025)

Shapley-Inspired Feature Weighting in k-means with No Additional Hyperparameters. - Richard J. Fawley; Renato Cordeiro de Amorim (CoRR, 2025)