Eduardo R. Hruschka

According to our database1, Eduardo R. Hruschka authored at least 92 papers between 1999 and 2018.

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

Timeline

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Bibliography

2018
Online Orthogonal Regression Based on a Regularized Squared Loss.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Classification with Multi-Modal Classes Using Evolutionary Algorithms and Constrained Clustering.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

Time Series Decomposition Using Spring System Applied on Phase Spaces.
Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017
An evolutionary algorithm for clustering data streams with a variable number of clusters.
Expert Syst. Appl., 2017

2016
A Support System for Clustering Data Streams with a Variable Number of Clusters.
TAAS, 2016

Using unsupervised information to improve semi-supervised tweet sentiment classification.
Inf. Sci., 2016

Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: A comparison of meta-features.
Neurocomputing, 2016

Evolving Gaussian Mixture Models with Splitting and Merging Mutation Operators.
Evolutionary Computation, 2016

A Survey and Comparative Study of Tweet Sentiment Analysis via Semi-Supervised Learning.
ACM Comput. Surv., 2016

2015
Interactive textual feature selection for consensus clustering.
Pattern Recognition Letters, 2015

Simultaneous co-clustering and learning to address the cold start problem in recommender systems.
Knowl.-Based Syst., 2015

A differential evolution algorithm to optimise the combination of classifier and cluster ensembles.
IJBIC, 2015

Using metaheuristics to optimize the combination of classifier and cluster ensembles.
Integrated Computer-Aided Engineering, 2015

2014
An Optimization Framework for Combining Ensembles of Classifiers and Clusterers with Applications to Nontransductive Semisupervised Learning and Transfer Learning.
TKDD, 2014

Tweet sentiment analysis with classifier ensembles.
Decision Support Systems, 2014

Biocom_Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble.
Proceedings of the 8th International Workshop on Semantic Evaluation, 2014

Privileged Information for Hierarchical Document Clustering: A Metric Learning Approach.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Combining Classification and Clustering for Tweet Sentiment Analysis.
Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

2013
Competitive Learning With Pairwise Constraints.
IEEE Trans. Neural Netw. Learning Syst., 2013

Document Clustering for Forensic Analysis: An Approach for Improving Computer Inspection.
IEEE Trans. Information Forensics and Security, 2013

Hierarchical Bottom-Up Safe Semi-Supervised Support Vector Machines for Multi-Class Transductive Learning.
JIDM, 2013

A study of K-Means-based algorithms for constrained clustering.
Intell. Data Anal., 2013

An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks.
Data Knowl. Eng., 2013

Data stream clustering: A survey.
ACM Comput. Surv., 2013

Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Using Both Latent and Supervised Shared Topics for Multitask Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Unsupervised learning of Gaussian Mixture Models: Evolutionary Create and Eliminate for Expectation Maximization algorithm.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2012
Collaborative Fuzzy Clustering Algorithms: Some Refinements and Design Guidelines.
IEEE Trans. Fuzzy Systems, 2012

Transfer Learning with Cluster Ensembles.
Proceedings of the Unsupervised and Transfer Learning, 2012

A Semi-supervised Approach to Estimate the Number of Clusters per Class.
Proceedings of the 2012 Brazilian Symposium on Neural Networks, 2012

On the Use of Consensus Clustering for Incremental Learning of Topic Hierarchies.
Proceedings of the Advances in Artificial Intelligence - SBIA 2012, 2012

A Meta-Learning Approach to Select Meta-Heuristics for the Traveling Salesman Problem Using MLP-Based Label Ranking.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

2011
A Bayesian imputation method for a clustering genetic algorithm.
J. Comput. Meth. in Science and Engineering, 2011

Towards improving cluster-based feature selection with a simplified silhouette filter.
Inf. Sci., 2011

Selection of algorithms to solve traveling salesman problems using meta-learning.
Int. J. Hybrid Intell. Syst., 2011

Bayesian network classifiers: Beyond classification accuracy.
Intell. Data Anal., 2011

Efficiency issues of evolutionary k-means.
Appl. Soft Comput., 2011

A Privacy-Aware Bayesian Approach for Combining Classifier and Cluster Ensembles.
Proceedings of the PASSAT/SocialCom 2011, Privacy, 2011

C 3E: A Framework for Combining Ensembles of Classifiers and Clusterers.
Proceedings of the Multiple Classifier Systems - 10th International Workshop, 2011

Extending k-Means-Based Algorithms for Evolving Data Streams with Variable Number of Clusters.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Document Clustering for Forensic Computing: An Approach for Improving Computer Inspection.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Using Meta-learning to Recommend Meta-heuristics for the Traveling Salesman Problem.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Splitting and Merging Gaussian Mixture Model Components: An Evolutionary Approach.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Distributed Fuzzy Clustering with Automatic Detection of the Number of Clusters.
Proceedings of the International Symposium on Distributed Computing and Artificial Intelligence, 2011

2010
Relative clustering validity criteria: A comparative overview.
Statistical Analysis and Data Mining, 2010

Using Meta-learning to Classify Traveling Salesman Problems.
Proceedings of the 11th Brazilian Symposium on Neural Networks (SBRN 2010), 2010

A Comparative Study on the Use of Correlation Coefficients for Redundant Feature Elimination.
Proceedings of the 11th Brazilian Symposium on Neural Networks (SBRN 2010), 2010

Fuzzy Clustering-Based Filter.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods, 2010

A Distance-Based Mutation Operator for learning Bayesian Network structures using Evolutionary Algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2009
Evolutionary Fuzzy Clustering: An Overview and Efficiency Issues.
Proceedings of the Foundations of Computational Intelligence, 2009

A Survey of Evolutionary Algorithms for Clustering.
IEEE Trans. Systems, Man, and Cybernetics, Part C, 2009

On the influence of imputation in classification: practical issues.
J. Exp. Theor. Artif. Intell., 2009

On comparing two sequences of numbers and its applications to clustering analysis.
Inf. Sci., 2009

On the efficiency of evolutionary fuzzy clustering.
J. Heuristics, 2009

On the Comparison of Relative Clustering Validity Criteria.
Proceedings of the SIAM International Conference on Data Mining, 2009

EACImpute: An Evolutionary Algorithm for Clustering-Based Imputation.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

An Experimental Study on Unsupervised Clustering-Based Feature Selection Methods.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

An Evolutionary Algorithm for Missing Values Substitution in Classification Tasks.
Proceedings of the Hybrid Artificial Intelligence Systems, 4th International Conference, 2009

A Cluster-Based Feature Selection Approach.
Proceedings of the Hybrid Artificial Intelligence Systems, 4th International Conference, 2009

2008
Genetic Clustering for Data Mining.
Proceedings of the Soft Computing for Knowledge Discovery and Data Mining, 2008

A Robust Methodology for Comparing Performances of Clustering Validity Criteria.
Proceedings of the Advances in Artificial Intelligence, 2008

2007
Exploiting idle cycles to execute data mining applications on clusters of PCs.
Journal of Systems and Software, 2007

Bayesian networks for imputation in classification problems.
J. Intell. Inf. Syst., 2007

A Fuzzy Variant of an Evolutionary Algorithm for Clustering.
Proceedings of the FUZZ-IEEE 2007, 2007

2006
Bayesian Feature Selection for Clustering Problems.
JIKM, 2006

Evolving clusters in gene-expression data.
Inf. Sci., 2006

Extracting rules from multilayer perceptrons in classification problems: A clustering-based approach.
Neurocomputing, 2006

A fuzzy extension of the silhouette width criterion for cluster analysis.
Fuzzy Sets and Systems, 2006

Towards a Fast Evolutionary Algorithm for Clustering.
Proceedings of the IEEE International Conference on Evolutionary Computation, 2006

2005
Towards Improving Clustering Ants: An Adaptive Ant Clustering Algorithm.
Informatica (Slovenia), 2005

Applying Bayesian Networks for Meteorological Data Mining.
Proceedings of the Applications and Innovations in Intelligent Systems XIII, 2005

Missing Values Imputation for a Clustering Genetic Algorithm.
Proceedings of the Advances in Natural Computation, First International Conference, 2005

Feature Selection for Clustering Problems: a Hybrid Algorithm that Iterates Between k-means and a Bayesian Filter.
Proceedings of the 5th International Conference on Hybrid Intelligent Systems (HIS 2005), 2005

Naive Bayes as an Imputation Tool for Classification Problems.
Proceedings of the 5th International Conference on Hybrid Intelligent Systems (HIS 2005), 2005

Feature Selection for Cluster Analysis: an Approach Based on the Simplified Silhouette Criterion.
Proceedings of the 2005 International Conference on Computational Intelligence for Modelling Control and Automation (CIMCA 2005), 2005

2004
Inhambu: Data Mining Using Idle Cycles in Clusters of PCs.
Proceedings of the Network and Parallel Computing, IFIP International Conference, 2004

TermitAnt: An Ant Clustering Algorithm Improved by Ideas from Termite Colonies.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

Evolutionary Algorithms for Clustering Gene-Expression Data.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

Running Data Mining Applications on the Grid: A Bag-of-Tasks Approach.
Proceedings of the Computational Science and Its Applications, 2004

Improving the Efficiency of a Clustering Genetic Algorithm.
Proceedings of the Advances in Artificial Intelligence, 2004

Evolutionary search for optimal fuzzy c-means clustering.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2004

A Scheduling Algorithm for Running Bag-of-Tasks Data Mining Applications on the Grid.
Proceedings of the Euro-Par 2004 Parallel Processing, 2004

Towards Efficient Imputation by Nearest-Neighbors: A Clustering-Based Approach.
Proceedings of the AI 2004: Advances in Artificial Intelligence, 2004

Feature Selection by Bayesian Networks.
Proceedings of the Advances in Artificial Intelligence, 2004

2003
A genetic algorithm for cluster analysis.
Intell. Data Anal., 2003

A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm.
Applied Artificial Intelligence, 2003

A Nearest-Neighbor Method as a Data Preparation Tool for a Clustering Genetic Algorithm.
Proceedings of the XVIII Simpósio Brasileiro de Bancos de Dados, 2003

Evaluating a Nearest-Neighbor Method to Substitute Continuous Missing Values.
Proceedings of the AI 2003: Advances in Artificial Intelligence, 2003

2002
A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm.
Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002

2000
A clustering algorithm for extracting rules from supervised neural network models in data mining tasks.
Int. J. Comput. Syst. Signal, 2000

Applying a Clustering Genetic Algorithm for Extracting Rules from a Supervised Neural Network.
IJCNN (3), 2000

1999
Rule extraction from neural networks: modified RX algorithm.
Proceedings of the International Joint Conference Neural Networks, 1999


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