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Alberto Cano 0001
Alberto Cano Rojas
Person information
- affiliation: Virginia Commonwealth University, Richmond, VA, USA
- affiliation: University of Córdoba, Spain
Other persons with the same name
- Alberto Cano 0002 (aka: Alberto Cano Pérez) — Universitat Politècnica de Catalunya, Barcelona, Spain
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2020 – today
- 2024
- [j57]William C. Sleeman, Martha I. Roseberry, Preetam Ghosh, Alberto Cano, Bartosz Krawczyk:
Improved KD-tree based imbalanced big data classification and oversampling for MapReduce platforms. Appl. Intell. 54(23): 12558-12575 (2024) - [j56]Youcef Djenouri, Ahmed Nabil Belbachir, Alberto Cano, Asma Belhadi:
Spatio-temporal visual learning for home-based monitoring. Inf. Fusion 101: 101984 (2024) - [j55]Gabriel Jonas Aguiar, Alberto Cano
:
Dynamic budget allocation for sparsely labeled drifting data streams. Inf. Sci. 654: 119821 (2024) - [j54]Gabriel Jonas Aguiar
A comprehensive analysis of concept drift locality in data streams. Knowl. Based Syst. 289: 111535 (2024) - [j53]Aurora Esteban
Hoeffding adaptive trees for multi-label classification on data streams. Knowl. Based Syst. 304: 112561 (2024) - [j52]Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework. Mach. Learn. 113(7): 4165-4243 (2024) - [c28]Pamela Buñay-Guisñan, Juan Alfonso Lara, Alberto Cano, Rebeca Cerezo, Cristóbal Romero:
Easing the Prediction of Student Dropout for everyone integration AutoML and Explainable Artificial Intelligence. EDM 2024 - [c27]Youcef Djenouri, Ahmed Nabil Belbachir, Gautam Srivastava, Alberto Cano:
Vision-based Spatiotemporal Learning for Human Activity Recognition. IJCNN 2024: 1-8 - [i5]Teresa Salazar, Helder Araújo, Alberto Cano, Pedro Henriques Abreu:
A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future Research. CoRR abs/2410.03855 (2024) - [i4]Aurora Esteban, Alberto Cano, Amelia Zafra, Sebastián Ventura:
Hoeffding adaptive trees for multi-label classification on data streams. CoRR abs/2410.20242 (2024) - 2023
- [j51]Vinicius Eiji Martins
Meta-learning for dynamic tuning of active learning on stream classification. Pattern Recognit. 138: 109359 (2023) - [c26]Gabriel Jonas Aguiar, Alberto Cano:
Enhancing Concept Drift Detection in Drifting and Imbalanced Data Streams through Meta-Learning. IEEE Big Data 2023: 2648-2657 - [c25]Gabriel Jonas Aguiar
An active learning budget-based oversampling approach for partially labeled multi-class imbalanced data streams. SAC 2023: 382-389 - [c24]Martha I. Roseberry
Aging and rejuvenating strategies for fading windows in multi-label classification on data streams. SAC 2023: 390-397 - [i3]Gabriel Jonas Aguiar, Alberto Cano:
A comprehensive analysis of concept drift locality in data streams. CoRR abs/2311.06396 (2023) - 2022
- [j50]Youcef Djenouri
An ontology matching approach for semantic modeling: A case study in smart cities. Comput. Intell. 38(3): 876-902 (2022) - [j49]Gavin Alberghini, Sylvio Barbon Junior
Adaptive ensemble of self-adjusting nearest neighbor subspaces for multi-label drifting data streams. Neurocomputing 481: 228-248 (2022) - [j48]Alberto Cano
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams. Mach. Learn. 111(7): 2561-2599 (2022) - [j47]Abhay Srivastava, Alberto Cano
Analysis and forecasting of rivers pH level using deep learning. Prog. Artif. Intell. 11(2): 181-191 (2022) - [j46]Asma Belhadi, Youcef Djenouri
Hybrid Group Anomaly Detection for Sequence Data: Application to Trajectory Data Analytics. IEEE Trans. Intell. Transp. Syst. 23(7): 9346-9357 (2022) - [c23]João Roberto Bertini Junior, Alberto Cano:
An Explainable Classifier based on Genetically Evolved Graph Structures. CEC 2022: 1-8 - [i2]Gabriel Jonas Aguiar, Bartosz Krawczyk, Alberto Cano:
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework. CoRR abs/2204.03719 (2022) - 2021
- [j45]Martha I. Roseberry, Bartosz Krawczyk, Youcef Djenouri
Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams. Neurocomputing 442: 10-25 (2021) - [j44]Ricardo Petri Silva
Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction. Sensors 21(21): 7333 (2021) - [j43]Asma Belhadi, Youcef Djenouri
A Two-Phase Anomaly Detection Model for Secure Intelligent Transportation Ride-Hailing Trajectories. IEEE Trans. Intell. Transp. Syst. 22(7): 4496-4506 (2021) - [c22]Bartosz Krawczyk, Alberto Cano:
Locally Linear Support Vector Machines for Imbalanced Data Classification. PAKDD (1) 2021: 616-628 - 2020
- [j42]Asma Belhadi
Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem. IEEE Access 8: 10569-10583 (2020) - [j41]Asma Belhadi, Youcef Djenouri
A Data-Driven Approach for Twitter Hashtag Recommendation. IEEE Access 8: 79182-79191 (2020) - [j40]Youcef Djenouri
When the Decomposition Meets the Constraint Satisfaction Problem. IEEE Access 8: 207034-207043 (2020) - [j39]Asma Belhadi, Youcef Djenouri
A general-purpose distributed pattern mining system. Appl. Intell. 50(9): 2647-2662 (2020) - [j38]Jorge Gonzalez-Lopez, Sebastián Ventura, Alberto Cano:
Distributed multi-label feature selection using individual mutual information measures. Knowl. Based Syst. 188 (2020) - [j37]Alberto Cano
Kappa Updated Ensemble for drifting data stream mining. Mach. Learn. 109(1): 175-218 (2020) - [j36]Hung T. Nguyen
Blocking Self-Avoiding Walks Stops Cyber-Epidemics: A Scalable GPU-Based Approach. IEEE Trans. Knowl. Data Eng. 32(7): 1263-1275 (2020) - [j35]Asma Belhadi, Youcef Djenouri
Trajectory Outlier Detection: Algorithms, Taxonomies, Evaluation, and Open Challenges. ACM Trans. Manag. Inf. Syst. 11(3): 16:1-16:29 (2020) - [j34]Jorge Gonzalez-Lopez, Sebastián Ventura
Distributed Selection of Continuous Features in Multilabel Classification Using Mutual Information. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2280-2293 (2020)
2010 – 2019
- 2019
- [j33]Youcef Djenouri
Adapted K-Nearest Neighbors for Detecting Anomalies on Spatio-Temporal Traffic Flow. IEEE Access 7: 10015-10027 (2019) - [j32]Youcef Djenouri
A Survey on Urban Traffic Anomalies Detection Algorithms. IEEE Access 7: 12192-12205 (2019) - [j31]Przemyslaw Skryjomski
Speeding up k-Nearest Neighbors classifier for large-scale multi-label learning on GPUs. Neurocomputing 354: 10-19 (2019) - [j30]Youcef Djenouri
Exploiting GPU and cluster parallelism in single scan frequent itemset mining. Inf. Sci. 496: 363-377 (2019) - [j29]Alberto Cano
Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams. Pattern Recognit. 87: 248-268 (2019) - [j28]Martha I. Roseberry, Bartosz Krawczyk, Alberto Cano
Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams. ACM Trans. Knowl. Discov. Data 13(6): 60:1-60:31 (2019) - [j27]Alberto Cano
Interpretable Multiview Early Warning System Adapted to Underrepresented Student Populations. IEEE Trans. Learn. Technol. 12(2): 198-211 (2019) - [c21]Lukasz Korycki, Alberto Cano, Bartosz Krawczyk:
Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams. IEEE BigData 2019: 2334-2343 - [c20]Jorge Gonzalez-Lopez, Sebastián Ventura, Alberto Cano:
ARFF Data Source Library for Distributed Single/Multiple Instance, Single/Multiple Output Learning on Apache Spark. ICCS (3) 2019: 173-179 - [c19]Bartosz Krawczyk, Alberto Cano:
Adaptive Ensemble Active Learning for Drifting Data Stream Mining. IJCAI 2019: 2763-2771 - [c18]Jose M. Moyano
Speeding Up Classifier Chains in Multi-label Classification. IoTBDS 2019: 29-37 - 2018
- [j26]Gabriella Melki
OLLAWV: OnLine Learning Algorithm using Worst-Violators. Appl. Soft Comput. 66: 384-393 (2018) - [j25]Bartosz Krawczyk
Online ensemble learning with abstaining classifiers for drifting and noisy data streams. Appl. Soft Comput. 68: 677-692 (2018) - [j24]Jorge Gonzalez-Lopez, Sebastián Ventura
Distributed nearest neighbor classification for large-scale multi-label data on spark. Future Gener. Comput. Syst. 87: 66-82 (2018) - [j23]Oscar Gabriel Reyes Pupo, Alberto Cano, Habib M. Fardoun, Sebastián Ventura:
A locally weighted learning method based on a data gravitation model for multi-target regression. Int. J. Comput. Intell. Syst. 11(1): 282-295 (2018) - [j22]Alberto Cano Rojas
Parallelization strategies for markerless human motion capture. J. Real Time Image Process. 14(2): 453-467 (2018) - [j21]Gabriella Melki
MIRSVM: Multi-instance support vector machine with bag representatives. Pattern Recognit. 79: 228-241 (2018) - [j20]Alberto Cano
A survey on graphic processing unit computing for large-scale data mining. WIREs Data Mining Knowl. Discov. 8(1) (2018) - [c17]Alberto Cano, Bartosz Krawczyk:
Learning Classification Rules with Differential Evolution for High-Speed Data Stream Mining on GPU s. CEC 2018: 1-8 - [c16]Bartosz Krawczyk, Alberto Cano, Michal Wozniak
Selecting local ensembles for multi-class imbalanced data classification. IJCNN 2018: 1-8 - [c15]Martha I. Roseberry, Alberto Cano:
Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams. LIDTA@ECML/PKDD 2018: 23-37 - 2017
- [j19]Gabriella Melki
Multi-target support vector regression via correlation regressor chains. Inf. Sci. 415: 53-69 (2017) - [j18]Alberto Cano
Extremely high-dimensional optimization with MapReduce: Scaling functions and algorithm. Inf. Sci. 415: 110-127 (2017) - [j17]Alberto Cano
An ensemble approach to multi-view multi-instance learning. Knowl. Based Syst. 136: 46-57 (2017) - [j16]Alberto Cano
Multi-objective genetic programming for feature extraction and data visualization. Soft Comput. 21(8): 2069-2089 (2017) - [c14]Amy L. Olex, Alberto Cano, Bridget T. McInnes:
Parsing MetaMap Files in Hadoop. AMIA 2017 - [c13]Bartosz Krawczyk, Bridget T. McInnes, Alberto Cano
Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization. HAIS 2017: 26-37 - [c12]Jorge Gonzalez-Lopez, Alberto Cano
Large-Scale Multi-label Ensemble Learning on Spark. TrustCom/BigDataSE/ICESS 2017: 893-900 - [i1]Hung T. Nguyen, Alberto Cano, Tam N. Vu, Thang N. Dinh:
Blocking Self-avoiding Walks Stops Cyber-epidemics: A Scalable GPU-based Approach. CoRR abs/1702.05854 (2017) - 2016
- [j15]Carlos Márquez-Vera, Alberto Cano
Early dropout prediction using data mining: a case study with high school students. Expert Syst. J. Knowl. Eng. 33(1): 107-124 (2016) - [j14]Alberto Cano
LAIM discretization for multi-label data. Inf. Sci. 330: 370-384 (2016) - [j13]José María Luna
Discovering useful patterns from multiple instance data. Inf. Sci. 357: 23-38 (2016) - [j12]Alberto Cano
ur-CAIM: improved CAIM discretization for unbalanced and balanced data. Soft Comput. 20(1): 173-188 (2016) - [j11]José María Luna
Speeding-Up Association Rule Mining With Inverted Index Compression. IEEE Trans. Cybern. 46(12): 3059-3072 (2016) - [c11]Alberto Cano
100 Million dimensions large-scale global optimization using distributed GPU computing. CEC 2016: 3566-3573 - [c10]Francisco Padillo, José María Luna
A Data Structure to Speed-Up Machine Learning Algorithms on Massive Datasets. HAIS 2016: 365-376 - 2015
- [j10]Alberto Cano, José María Luna, Amelia Zafra, Sebastián Ventura:
A classification module for genetic programming algorithms in JCLEC. J. Mach. Learn. Res. 16: 491-494 (2015) - [j9]Alberto Cano
Speeding up multiple instance learning classification rules on GPUs. Knowl. Inf. Syst. 44(1): 127-145 (2015) - [c9]David Pinheiro, Alberto Cano
Synthesis of In-Place Iterative Sorting Algorithms Using GP: A Comparison Between STGP, SFGP, G3P and GE. EPIA 2015: 305-310 - [r1]José María Luna
Genetic Programming for Mining Association Rules in Relational Database Environments. Handbook of Genetic Programming Applications 2015: 431-450 - 2014
- [j8]Alberto Cano
Parallel evaluation of Pittsburgh rule-based classifiers on GPUs. Neurocomputing 126: 45-57 (2014) - [j7]Alberto Cano
Scalable CAIM discretization on multiple GPUs using concurrent kernels. J. Supercomput. 69(1): 273-292 (2014) - [c8]Alberto Cano
GPU-parallel subtree interpreter for genetic programming. GECCO 2014: 887-894 - [c7]Juan A. Pedraza, Carlos García-Martínez
Classification Rule Mining with Iterated Greedy. HAIS 2014: 585-596 - 2013
- [j6]Carlos Márquez-Vera, Alberto Cano
Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data. Appl. Intell. 38(3): 315-330 (2013) - [j5]Alberto Cano
An interpretable classification rule mining algorithm. Inf. Sci. 240: 1-20 (2013) - [j4]Alberto Cano
Parallel multi-objective Ant Programming for classification using GPUs. J. Parallel Distributed Comput. 73(6): 713-728 (2013) - [j3]Alberto Cano
Weighted Data Gravitation Classification for Standard and Imbalanced Data. IEEE Trans. Cybern. 43(6): 1672-1687 (2013) - [j2]Alberto Cano
High performance evaluation of evolutionary-mined association rules on GPUs. J. Supercomput. 66(3): 1438-1461 (2013) - [c6]Alberto Cano
A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification. EuroGP 2013: 217-228 - 2012
- [j1]Alberto Cano
Speeding up the evaluation phase of GP classification algorithms on GPUs. Soft Comput. 16(2): 187-202 (2012) - [c5]Juan Luis Olmo
Binary and multiclass imbalanced classification using multi-objective ant programming. ISDA 2012: 70-76 - 2011
- [c4]Alberto Cano, Amelia Zafra
A Parallel Genetic Programming Algorithm for Classification. HAIS (1) 2011: 172-181 - [c3]Alberto Cano, José María Luna
JCLEC Meets WEKA! HAIS (1) 2011: 388-395 - [c2]Alberto Cano
An EP algorithm for learning highly interpretable classifiers. ISDA 2011: 325-330 - 2010
- [c1]Alberto Cano
Solving Classification Problems Using Genetic Programming Algorithms on GPUs. HAIS (2) 2010: 17-26
Coauthor Index
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last updated on 2024-12-26 00:49 CET by the dblp team
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