Alberto Cano

According to our database1, Alberto Cano authored at least 66 papers between 2010 and 2021.

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



In proceedings 
PhD thesis 


Online presence:



Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams.
Neurocomputing, 2021

Locally Linear Support Vector Machines for Imbalanced Data Classification.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Distributed Selection of Continuous Features in Multilabel Classification Using Mutual Information.
IEEE Trans. Neural Networks Learn. Syst., 2020

Trajectory Outlier Detection: Algorithms, Taxonomies, Evaluation, and Open Challenges.
ACM Trans. Manag. Inf. Syst., 2020

Blocking Self-Avoiding Walks Stops Cyber-Epidemics: A Scalable GPU-Based Approach.
IEEE Trans. Knowl. Data Eng., 2020

Kappa Updated Ensemble for drifting data stream mining.
Mach. Learn., 2020

Distributed multi-label feature selection using individual mutual information measures.
Knowl. Based Syst., 2020

A general-purpose distributed pattern mining system.
Appl. Intell., 2020

When the Decomposition Meets the Constraint Satisfaction Problem.
IEEE Access, 2020

Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem.
IEEE Access, 2020

A Data-Driven Approach for Twitter Hashtag Recommendation.
IEEE Access, 2020

Interpretable Multiview Early Warning System Adapted to Underrepresented Student Populations.
IEEE Trans. Learn. Technol., 2019

Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams.
ACM Trans. Knowl. Discov. Data, 2019

Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams.
Pattern Recognit., 2019

Exploiting GPU and cluster parallelism in single scan frequent itemset mining.
Inf. Sci., 2019

Speeding up <i>k</i>-Nearest Neighbors classifier for large-scale multi-label learning on GPUs.
Neurocomputing, 2019

A Survey on Urban Traffic Anomalies Detection Algorithms.
IEEE Access, 2019

Adapted K-Nearest Neighbors for Detecting Anomalies on Spatio-Temporal Traffic Flow.
IEEE Access, 2019

Speeding Up Classifier Chains in Multi-label Classification.
Proceedings of the 4th International Conference on Internet of Things, 2019

Adaptive Ensemble Active Learning for Drifting Data Stream Mining.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

ARFF Data Source Library for Distributed Single/Multiple Instance, Single/Multiple Output Learning on Apache Spark.
Proceedings of the Computational Science - ICCS 2019, 2019

Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams.
Proceedings of the 2019 IEEE International Conference on Big Data (Big Data), 2019

A survey on graphic processing unit computing for large-scale data mining.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2018

MIRSVM: Multi-instance support vector machine with bag representatives.
Pattern Recognit., 2018

Parallelization strategies for markerless human motion capture.
J. Real Time Image Process., 2018

A locally weighted learning method based on a data gravitation model for multi-target regression.
Int. J. Comput. Intell. Syst., 2018

Distributed nearest neighbor classification for large-scale multi-label data on spark.
Future Gener. Comput. Syst., 2018

OLLAWV: OnLine Learning Algorithm using Worst-Violators.
Appl. Soft Comput., 2018

Online ensemble learning with abstaining classifiers for drifting and noisy data streams.
Appl. Soft Comput., 2018

Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams.
Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Selecting local ensembles for multi-class imbalanced data classification.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Learning Classification Rules with Differential Evolution for High-Speed Data Stream Mining on GPU s.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

Multi-objective genetic programming for feature extraction and data visualization.
Soft Comput., 2017

An ensemble approach to multi-view multi-instance learning.
Knowl. Based Syst., 2017

Multi-target support vector regression via correlation regressor chains.
Inf. Sci., 2017

Extremely high-dimensional optimization with MapReduce: Scaling functions and algorithm.
Inf. Sci., 2017

Large-Scale Multi-label Ensemble Learning on Spark.
Proceedings of the 2017 IEEE Trustcom/BigDataSE/ICESS, Sydney, Australia, August 1-4, 2017, 2017

Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization.
Proceedings of the Hybrid Artificial Intelligent Systems - 12th International Conference, 2017

Parsing MetaMap Files in Hadoop.
Proceedings of the AMIA 2017, 2017

Speeding-Up Association Rule Mining With Inverted Index Compression.
IEEE Trans. Cybern., 2016

ur-CAIM: improved CAIM discretization for unbalanced and balanced data.
Soft Comput., 2016

Discovering useful patterns from multiple instance data.
Inf. Sci., 2016

LAIM discretization for multi-label data.
Inf. Sci., 2016

Early dropout prediction using data mining: a case study with high school students.
Expert Syst. J. Knowl. Eng., 2016

A Data Structure to Speed-Up Machine Learning Algorithms on Massive Datasets.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

100 Million dimensions large-scale global optimization using distributed GPU computing.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

Genetic Programming for Mining Association Rules in Relational Database Environments.
Proceedings of the Handbook of Genetic Programming Applications, 2015

Speeding up multiple instance learning classification rules on GPUs.
Knowl. Inf. Syst., 2015

A classification module for genetic programming algorithms in JCLEC.
J. Mach. Learn. Res., 2015

Synthesis of In-Place Iterative Sorting Algorithms Using GP: A Comparison Between STGP, SFGP, G3P and GE.
Proceedings of the Progress in Artificial Intelligence, 2015

Scalable CAIM discretization on multiple GPUs using concurrent kernels.
J. Supercomput., 2014

Parallel evaluation of Pittsburgh rule-based classifiers on GPUs.
Neurocomputing, 2014

Classification Rule Mining with Iterated Greedy.
Proceedings of the Hybrid Artificial Intelligence Systems - 9th International Conference, 2014

GPU-parallel subtree interpreter for genetic programming.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

High performance evaluation of evolutionary-mined association rules on GPUs.
J. Supercomput., 2013

Weighted Data Gravitation Classification for Standard and Imbalanced Data.
IEEE Trans. Cybern., 2013

Parallel multi-objective Ant Programming for classification using GPUs.
J. Parallel Distributed Comput., 2013

An interpretable classification rule mining algorithm.
Inf. Sci., 2013

Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data.
Appl. Intell., 2013

A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification.
Proceedings of the Genetic Programming - 16th European Conference, 2013

Speeding up the evaluation phase of GP classification algorithms on GPUs.
Soft Comput., 2012

Binary and multiclass imbalanced classification using multi-objective ant programming.
Proceedings of the 12th International Conference on Intelligent Systems Design and Applications, 2012

An EP algorithm for learning highly interpretable classifiers.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

A Parallel Genetic Programming Algorithm for Classification.
Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011

Solving Classification Problems Using Genetic Programming Algorithms on GPUs.
Proceedings of the Hybrid Artificial Intelligence Systems, 5th International Conference, 2010