Eduardo R. Hruschka

Publication Activity (10 Years)

Years Active: 1999-2019
Publications (10 Years): 7

Top Topics

Transductive Learning

Sentiment Analysis

Consensus Clustering

Cluster Ensemble

Top Venues

ACM Comput. Surv.

Decis. Support Syst.

Publications

Felipe S. L. G. Duarte, Ricardo Araújo Rios, Eduardo R. Hruschka, Rodrigo Fernandes de Mello
Decomposing time series into deterministic and stochastic influences: A survey. Digit. Signal Process. 95 (2019)
Luiz F. S. Coletta, Moacir Ponti, Eduardo R. Hruschka, Ayan Acharya, Joydeep Ghosh
Combining clustering and active learning for the detection and learning of new image classes. Neurocomputing 358 (2019)
Thiago F. Covoes, Eduardo R. Hruschka
Classification with Multi-Modal Classes Using Evolutionary Algorithms and Constrained Clustering. CEC (2018)
Roberto Souza, Saul C. Leite, Wagner Meira Jr., Eduardo R. Hruschka
Online Orthogonal Regression Based on a Regularized Squared Loss. ICMLA (2018)
Jorge Y. Kanda, André C. P. L. F. de Carvalho, Eduardo R. Hruschka, Carlos Soares, Pavel Brazdil
Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: A comparison of meta-features. Neurocomputing 205 (2016)
Nádia Félix Felipe da Silva, Luiz F. S. Coletta, Eduardo R. Hruschka
A Survey and Comparative Study of Tweet Sentiment Analysis via Semi-Supervised Learning. ACM Comput. Surv. 49 (1) (2016)
Nádia Félix Felipe da Silva, Luiz F. S. Coletta, Eduardo R. Hruschka, Estevam R. Hruschka Jr.
Using unsupervised information to improve semi-supervised tweet sentiment classification. Inf. Sci. (2016)
Luiz F. S. Coletta, Eduardo R. Hruschka, Ayan Acharya, Joydeep Ghosh
Using metaheuristics to optimize the combination of classifier and cluster ensembles. Integr. Comput. Aided Eng. 22 (3) (2015)
Geraldo N. Correa, Ricardo M. Marcacini, Eduardo R. Hruschka, Solange Oliveira Rezende
Interactive textual feature selection for consensus clustering. Pattern Recognit. Lett. 52 (2015)
Ricardo Marcondes Marcacini, Marcos Aurélio Domingues, Eduardo R. Hruschka, Solange Oliveira Rezende
Privileged Information for Hierarchical Document Clustering: A Metric Learning Approach. ICPR (2014)
Nádia Félix F. da Silva, Estevam R. Hruschka Jr., Eduardo R. Hruschka
Biocom_Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble. SemEval@COLING (2014)
Nádia Félix F. da Silva, Eduardo R. Hruschka, Estevam R. Hruschka Jr.
Tweet sentiment analysis with classifier ensembles. Decis. Support Syst. 66 (2014)
Luiz Fernando Sommaggio Coletta, Nádia Félix F. da Silva, Eduardo R. Hruschka, Estevam R. Hruschka Jr.
Combining Classification and Clustering for Tweet Sentiment Analysis. BRACIS (2014)
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya
An Optimization Framework for Combining Ensembles of Classifiers and Clusterers with Applications to Nontransductive Semisupervised Learning and Transfer Learning. ACM Trans. Knowl. Discov. Data 9 (1) (2014)
Jonathan de Andrade Silva, Eduardo R. Hruschka
An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks. Data Knowl. Eng. 84 (2013)
Ayan Acharya, Joydeep Ghosh, Eduardo R. Hruschka, Jean-David Ruvini, Badrul Sarwar
Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning. SDM (2013)
Thiago F. Covoes, Eduardo R. Hruschka, Joydeep Ghosh
A study of K-Means-based algorithms for constrained clustering. Intell. Data Anal. 17 (3) (2013)
Ayan Acharya, Aditya Rawal, Raymond J. Mooney, Eduardo R. Hruschka
Using Both Latent and Supervised Shared Topics for Multitask Learning. ECML/PKDD (2) (2013)
Luís Filipe da Cruz Nassif, Eduardo R. Hruschka
Document Clustering for Forensic Analysis: An Approach for Improving Computer Inspection. IEEE Trans. Inf. Forensics Secur. 8 (1) (2013)
Thiago F. Covoes, Rodrigo C. Barros, Tiago Silva da Silva, Eduardo R. Hruschka, André Carlos Ponce de Leon Ferreira de Carvalho
Hierarchical Bottom-Up Safe Semi-Supervised Support Vector Machines for Multi-Class Transductive Learning. J. Inf. Data Manag. 4 (3) (2013)
Thiago F. Covoes, Eduardo R. Hruschka
Unsupervised learning of Gaussian Mixture Models: Evolutionary Create and Eliminate for Expectation Maximization algorithm. IEEE Congress on Evolutionary Computation (2013)
Jonathan de Andrade Silva, Elaine R. Faria, Rodrigo C. Barros, Eduardo R. Hruschka, André Carlos Ponce de Leon Ferreira de Carvalho, João Gama
Data stream clustering: A survey. ACM Comput. Surv. 46 (1) (2013)
Thiago F. Covoes, Eduardo R. Hruschka, Joydeep Ghosh
Competitive Learning With Pairwise Constraints. IEEE Trans. Neural Networks Learn. Syst. 24 (1) (2013)
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh
A Privacy-Aware Bayesian Approach for Combining Classifier and Cluster Ensembles CoRR (2012)
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Badrul Sarwar, Jean-David Ruvini
Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning CoRR (2012)
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya
Transfer Learning with Cluster Ensembles. ICML Unsupervised and Transfer Learning (2012)
Jorge Y. Kanda, Carlos Soares, Eduardo R. Hruschka, André Carlos Ponce de Leon Ferreira de Carvalho
A Meta-Learning Approach to Select Meta-Heuristics for the Traveling Salesman Problem Using MLP-Based Label Ranking. ICONIP (3) (2012)
Luiz F. S. Coletta, Lucas Vendramin, Eduardo R. Hruschka, Ricardo J. G. B. Campello, Witold Pedrycz
Collaborative Fuzzy Clustering Algorithms: Some Refinements and Design Guidelines. IEEE Trans. Fuzzy Syst. 20 (3) (2012)
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya
An Optimization Framework for Semi-Supervised and Transfer Learning using Multiple Classifiers and Clusterers CoRR (2012)
Ricardo M. Marcacini, Eduardo R. Hruschka, Solange O. Rezende
On the Use of Consensus Clustering for Incremental Learning of Topic Hierarchies. SBIA (2012)
Davidson M. Sestaro, Thiago F. Covoes, Eduardo R. Hruschka
A Semi-supervised Approach to Estimate the Number of Clusters per Class. SBRN (2012)
Luís Filipe da Cruz Nassif, Eduardo R. Hruschka
Document Clustering for Forensic Computing: An Approach for Improving Computer Inspection. ICMLA (1) (2011)
Jorge Y. Kanda, André Carlos Ponce de Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares
Using Meta-learning to Recommend Meta-heuristics for the Traveling Salesman Problem. ICMLA (1) (2011)
Thiago F. Covoes, Eduardo R. Hruschka
Splitting and Merging Gaussian Mixture Model Components: An Evolutionary Approach. ICMLA (1) (2011)
Jonathan de Andrade Silva, Eduardo R. Hruschka
Extending k-Means-Based Algorithms for Evolving Data Streams with Variable Number of Clusters. ICMLA (2) (2011)
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh
A Privacy-Aware Bayesian Approach for Combining Classifier and Cluster Ensembles. SocialCom/PASSAT (2011)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Bayesian network classifiers: Beyond classification accuracy. Intell. Data Anal. 15 (3) (2011)
Thiago F. Covoes, Eduardo R. Hruschka
Towards improving cluster-based feature selection with a simplified silhouette filter. Inf. Sci. 181 (18) (2011)
Jorge Y. Kanda, André Carlos Ponce de Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares
Selection of algorithms to solve traveling salesman problems using meta-learning. Int. J. Hybrid Intell. Syst. 8 (3) (2011)
Lucas Vendramin, Ricardo José Gabrielli Barreto Campello, Luiz F. S. Coletta, Eduardo R. Hruschka
Distributed Fuzzy Clustering with Automatic Detection of the Number of Clusters. DCAI (2011)
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya
C 3E: A Framework for Combining Ensembles of Classifiers and Clusterers. MCS (2011)
Murilo Coelho Naldi, Ricardo J. G. B. Campello, Eduardo R. Hruschka, André C. P. L. F. de Carvalho
Efficiency issues of evolutionary k-means. Appl. Soft Comput. 11 (2) (2011)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Bayesian imputation method for a clustering genetic algorithm. J. Comput. Methods Sci. Eng. 11 (4) (2011)
Jorge Y. Kanda, André Carlos Ponce de Leon Ferreira de Carvalho, Eduardo R. Hruschka, Carlos Soares
Using Meta-learning to Classify Traveling Salesman Problems. SBRN (2010)
Lucas Vendramin, Ricardo J. G. B. Campello, Eduardo R. Hruschka
Relative clustering validity criteria: A comparative overview. Stat. Anal. Data Min. 3 (4) (2010)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Distance-Based Mutation Operator for learning Bayesian Network structures using Evolutionary Algorithms. IEEE Congress on Evolutionary Computation (2010)
Luiz F. S. Coletta, Eduardo R. Hruschka, Thiago F. Covoes, Ricardo J. G. B. Campello
Fuzzy Clustering-Based Filter. IPMU (1) (2010)
Pablo A. Jaskowiak, Ricardo J. G. B. Campello, Thiago F. Covoes, Eduardo R. Hruschka
A Comparative Study on the Use of Correlation Coefficients for Redundant Feature Elimination. SBRN (2010)
Ricardo J. G. B. Campello, Eduardo R. Hruschka, Vinicius S. Alves
On the efficiency of evolutionary fuzzy clustering. J. Heuristics 15 (1) (2009)
Thiago F. Covoes, Eduardo R. Hruschka, Leandro Nunes de Castro, Átila M. Santos
A Cluster-Based Feature Selection Approach. HAIS (2009)
Eduardo R. Hruschka, Ricardo José Gabrielli Barreto Campello, Alex Alves Freitas, André Carlos Ponce de Leon Ferreira de Carvalho
A Survey of Evolutionary Algorithms for Clustering. IEEE Trans. Syst. Man Cybern. Part C 39 (2) (2009)
Lucas Vendramin, Ricardo J. G. B. Campello, Eduardo R. Hruschka
On the Comparison of Relative Clustering Validity Criteria. SDM (2009)
Eduardo R. Hruschka, Antonio J. T. Garcia, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
On the influence of imputation in classification: practical issues. J. Exp. Theor. Artif. Intell. 21 (1) (2009)
Ricardo José Gabrielli Barreto Campello, Eduardo R. Hruschka
On comparing two sequences of numbers and its applications to clustering analysis. Inf. Sci. 179 (8) (2009)
Jonathan de Andrade Silva, Eduardo R. Hruschka
An Evolutionary Algorithm for Missing Values Substitution in Classification Tasks. HAIS (2009)
Thiago F. Covoes, Eduardo R. Hruschka
An Experimental Study on Unsupervised Clustering-Based Feature Selection Methods. ISDA (2009)
Jonathan de Andrade Silva, Eduardo R. Hruschka
EACImpute: An Evolutionary Algorithm for Clustering-Based Imputation. ISDA (2009)
Lucas Vendramin, Ricardo J. G. B. Campello, Eduardo R. Hruschka
A Robust Methodology for Comparing Performances of Clustering Validity Criteria. SBIA (2008)
Vinicius S. Alves, Ricardo J. G. B. Campello, Eduardo R. Hruschka
A Fuzzy Variant of an Evolutionary Algorithm for Clustering. FUZZ-IEEE (2007)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Bayesian networks for imputation in classification problems. J. Intell. Inf. Syst. 29 (3) (2007)
Hermes Senger, Eduardo R. Hruschka, Fabrício Alves Barbosa da Silva, Liria Matsumoto Sato, Calebe De Paula Bianchini, Bruno F. Jerosch
Exploiting idle cycles to execute data mining applications on clusters of PCs. J. Syst. Softw. 80 (5) (2007)
Eduardo R. Hruschka, Nelson F. F. Ebecken
Extracting rules from multilayer perceptrons in classification problems: A clustering-based approach. Neurocomputing 70 (1-3) (2006)
Eduardo R. Hruschka, Ricardo J. G. B. Campello, Leandro Nunes de Castro
Evolving clusters in gene-expression data. Inf. Sci. 176 (13) (2006)
Vinicius S. Alves, Ricardo J. G. B. Campello, Eduardo R. Hruschka
Towards a Fast Evolutionary Algorithm for Clustering. IEEE Congress on Evolutionary Computation (2006)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Thiago F. Covoes, Nelson F. F. Ebecken
Bayesian Feature Selection for Clustering Problems. J. Inf. Knowl. Manag. 5 (4) (2006)
Ricardo J. G. B. Campello, Eduardo R. Hruschka
A fuzzy extension of the silhouette width criterion for cluster analysis. Fuzzy Sets Syst. 157 (21) (2006)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Applying Bayesian Networks for Meteorological Data Mining. SGAI Conf. (Applications) (2005)
Eduardo R. Hruschka, Thiago F. Covoes, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Feature Selection for Clustering Problems: a Hybrid Algorithm that Iterates Between k-means and a Bayesian Filter. HIS (2005)
Antonio J. T. Garcia, Eduardo R. Hruschka
Naive Bayes as an Imputation Tool for Classification Problems. HIS (2005)
André L. Vizine, Leandro Nunes de Castro, Eduardo R. Hruschka, Ricardo R. Gudwin
Towards Improving Clustering Ants: An Adaptive Ant Clustering Algorithm. Informatica (Slovenia) 29 (2) (2005)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Missing Values Imputation for a Clustering Genetic Algorithm. ICNC (3) (2005)
Eduardo R. Hruschka, Thiago F. Covoes
Feature Selection for Cluster Analysis: an Approach Based on the Simplified Silhouette Criterion. CIMCA/IAWTIC (2005)
Hermes Senger, Eduardo R. Hruschka, Fabrício Alves Barbosa da Silva, Liria Matsumoto Sato, Calebe De Paula Bianchini, Marcelo D. Esperidiãao
Inhambu: Data Mining Using Idle Cycles in Clusters of PCs. NPC (2004)
Eduardo R. Hruschka, Ricardo J. G. B. Campello, Leandro Nunes de Castro
Evolutionary search for optimal fuzzy c-means clustering. FUZZ-IEEE (2004)
Eduardo R. Hruschka, Leandro Nunes de Castro, Ricardo J. G. B. Campello
Evolutionary Algorithms for Clustering Gene-Expression Data. ICDM (2004)
Vahid Sherafat, Leandro Nunes de Castro, Eduardo R. Hruschka
TermitAnt: An Ant Clustering Algorithm Improved by Ideas from Termite Colonies. ICONIP (2004)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Feature Selection by Bayesian Networks. Canadian Conference on AI (2004)
Eduardo R. Hruschka, Ricardo J. G. B. Campello, Leandro Nunes de Castro
Improving the Efficiency of a Clustering Genetic Algorithm. IBERAMIA (2004)
Fabrício Alves Barbosa da Silva, Sílvia Carvalho, Hermes Senger, Eduardo R. Hruschka, Cléver Ricardo Guareis de Farias
Running Data Mining Applications on the Grid: A Bag-of-Tasks Approach. ICCSA (2) (2004)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Towards Efficient Imputation by Nearest-Neighbors: A Clustering-Based Approach. Australian Conference on Artificial Intelligence (2004)
Fabrício Alves Barbosa da Silva, Sílvia Carvalho, Eduardo R. Hruschka
A Scheduling Algorithm for Running Bag-of-Tasks Data Mining Applications on the Grid. Euro-Par (2004)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Evaluating a Nearest-Neighbor Method to Substitute Continuous Missing Values. Australian Conference on Artificial Intelligence (2003)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm. Appl. Artif. Intell. 17 (5-6) (2003)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
A Nearest-Neighbor Method as a Data Preparation Tool for a Clustering Genetic Algorithm. SBBD (2003)
Eduardo R. Hruschka, Nelson F. F. Ebecken
A genetic algorithm for cluster analysis. Intell. Data Anal. 7 (1) (2003)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm. HIS (2002)
Eduardo R. Hruschka, Nelson F. F. Ebecken
Applying a Clustering Genetic Algorithm for Extracting Rules from a Supervised Neural Network. IJCNN (3) (2000)
Eduardo R. Hruschka, Nelson F. F. Ebecken
A clustering algorithm for extracting rules from supervised neural network models in data mining tasks. Int. J. Comput. Syst. Signals 1 (1) (2000)
Eduardo R. Hruschka, Nelson Francisco Favilla Ebecken
Rule extraction from neural networks: modified RX algorithm. IJCNN (1999)