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ORCIDRita P. Ribeiro
Rita Paula Ribeiro
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- affiliation: University of Porto, Portugal
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2020 – today
- 2025
[i11]Ehsan Aminian, João Gama, Rita P. Ribeiro:
Histogram approaches for imbalanced data streams regression. CoRR abs/2501.17568 (2025)- 2024
- [j12]João Gama, Rita P. Ribeiro
, Saulo Martiello Mastelini, Narjes Davari, Bruno Veloso:
From fault detection to anomaly explanation: A case study on predictive maintenance. J. Web Semant. 81: 100821 (2024) - [c51]César Andrade, Rita P. Ribeiro, João Gama:
Evaluating Short Text Stream Clustering on Large E-commerce Datasets. BRACIS (3) 2024: 245-259 - [c50]César Andrade, Rita P. Ribeiro, João Gama:
Community-Based Topic Modeling with Contextual Outlier Handling. CAEPIA 2024: 173-183 - [c49]Matías Molina, Bruno Veloso, Carlos Abreu Ferreira, Rita P. Ribeiro, João Gama:
More (Enough) Is Better: Towards Few-Shot Illegal Landfill Waste Segmentation. ECAI 2024: 4547-4554 - [c48]Rita P. Ribeiro:
Predictive Maintenance for Industry 4.0 & 5.0. EXPLAINS 2024: 9 - [c47]Bruna Alves, Ana Almeida, Catarina Silva, Daniela Pais, Rita P. Ribeiro, João Gama, José Maria Fernandes, Susana Brás, Raquel Sebastião:
Emotion-Enhanced Pain Assessment Protocol. HAR 2024: 385-400 - [c46]Matías Molina, Rita P. Ribeiro, Bruno Veloso, João Gama:
Super-Resolution Analysis for Landfill Waste Classification. IDA (1) 2024: 155-166 - [c45]Rita P. Ribeiro:
Predictive Maintenance for Industry 4.0 & 5.0. IJCCI 2024: 9 - [c44]Narjes Davari, Bruno Veloso, Rita Paula Ribeiro, João Manuel Portela da Gama:
Detecting and Explaining Anomalies in the Air Production Unit of a Train. SAC 2024: 358-364 - [c43]Maciej Mozolewski, Szymon Bobek, Rita P. Ribeiro, Grzegorz J. Nalepa, João Gama:
Towards Evaluation of Explainable Artificial Intelligence in Streaming Data. xAI (4) 2024: 145-168 - [i10]Matías Molina, Rita P. Ribeiro, Bruno Veloso, João Gama:
Super-Resolution Analysis for Landfill Waste Classification. CoRR abs/2404.01790 (2024) - [i9]João Gama, Rita P. Ribeiro, Saulo Martiello Mastelini, Narjes Davari, Bruno Veloso:
A Neuro-Symbolic Explainer for Rare Events: A Case Study on Predictive Maintenance. CoRR abs/2404.14455 (2024) - [i8]Sérgio M. Jesus, Pedro Saleiro, Inês Oliveira e Silva, Beatriz M. Jorge, Rita P. Ribeiro, João Gama, Pedro Bizarro, Rayid Ghani:
Aequitas Flow: Streamlining Fair ML Experimentation. CoRR abs/2405.05809 (2024) - [i7]Jakub Jakubowski, Natalia Wojak-Strzelecka, Rita P. Ribeiro, Sepideh Pashami, Szymon Bobek, João Gama, Grzegorz J. Nalepa:
Artificial Intelligence Approaches for Predictive Maintenance in the Steel Industry: A Survey. CoRR abs/2405.12785 (2024) - 2023
- [j11]Emanuel Sousa Tomé, Rita P. Ribeiro, Inês Dutra, Arlete Rodrigues:
An Online Anomaly Detection Approach for Fault Detection on Fire Alarm Systems. Sensors 23(10): 4902 (2023) - [c42]Thiago Andrade, Nirbhaya Shaji, Rita P. Ribeiro, João Gama:
Pollution Emission Patterns of Transportation in Porto, Portugal Through Network Analysis. EPIA (1) 2023: 215-226 - [c41]César Andrade, Rita P. Ribeiro, João Gama:
Topic Model with Contextual Outlier Handling: a Study on Electronic Invoice Product Descriptions. EPIA (1) 2023: 365-377 - [c40]João Gama, Slawomir Nowaczyk, Sepideh Pashami, Rita P. Ribeiro, Grzegorz J. Nalepa, Bruno Veloso:
XAI for Predictive Maintenance. KDD 2023: 5798-5799 - [c39]Inês Oliveira e Silva, Rita P. Ribeiro, João Gama:
Anomaly Detection in Pet Behavioural Data. PKDD/ECML Workshops (2) 2023: 137-153 - [c38]Marta Barbosa, Carolina Ribeiro, Filipe Gomes, Rita P. Ribeiro, João Gama:
Data Science for Fighting Environmental Crime. PKDD/ECML Workshops (2) 2023: 181-196 - [c37]Szymon Bobek, Slawomir Nowaczyk, João Gama, Sepideh Pashami, Rita P. Ribeiro, Zahra Taghiyarrenani, Bruno Veloso, Lala H. Rajaoarisoa, Maciej Szelazek, Grzegorz J. Nalepa:
Why Industry 5.0 Needs XAI 2.0? xAI (Late-breaking Work, Demos, Doctoral Consortium) 2023: 1-6 - [e9]Albert Bifet, Ana Carolina Lorena, Rita P. Ribeiro, João Gama, Pedro H. Abreu:
Discovery Science - 26th International Conference, DS 2023, Porto, Portugal, October 9-11, 2023, Proceedings. Lecture Notes in Computer Science 14276, Springer 2023, ISBN 978-3-031-45274-1 [contents] - [e8]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e7]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - [d3]Narjes Davari, Bruno Veloso, Rita P. Ribeiro, João Gama:
MetroPT-3 Dataset. UCI Machine Learning Repository, 2023
- [i6]Sepideh Pashami, Slawomir Nowaczyk, Yuantao Fan, Jakub Jakubowski, Nuno Paiva, Narjes Davari, Szymon Bobek, Samaneh Jamshidi, Hamid Sarmadi, Abdallah Alabdallah, Rita P. Ribeiro, Bruno Veloso, Moamar Sayed Mouchaweh, Lala H. Rajaoarisoa, Grzegorz J. Nalepa, João Gama:
Explainable Predictive Maintenance. CoRR abs/2306.05120 (2023) - 2022
- [j10]João Gama, Rita P. Ribeiro, Bruno Veloso:
Data-Driven Predictive Maintenance. IEEE Intell. Syst. 37(4): 27-29 (2022) - [c36]Anibal Silva, Rita P. Ribeiro, Nuno Moniz:
Model Optimization in Imbalanced Regression. DS 2022: 3-21 - [c35]Narjes Davari, Sepideh Pashami, Bruno Veloso, Slawomir Nowaczyk, Yuantao Fan, Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
A Fault Detection Framework Based on LSTM Autoencoder: A Case Study for Volvo Bus Data Set. IDA 2022: 39-52 - [c34]Nirbhaya Shaji, João Gama, Rita P. Ribeiro, Pedro Gomes:
Bank Statements to Network Features: Extracting Features Out of Time Series Using Visibility Graph. IDA 2022: 278-289 - [c33]Nádia Soares, João F. Gonçalves, Raquel Vasconcelos, Rita P. Ribeiro:
Combining Multiple Data Sources to Predict IUCN Conservation Status of Reptiles. IDA 2022: 302-314 - [c32]Sérgio M. Jesus, José Pombal, Duarte M. Alves, André Ferreira Cruz, Pedro Saleiro, Rita P. Ribeiro, João Gama, Pedro Bizarro:
Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation. NeurIPS 2022 - [c31]Rodrigo Salles, Jérôme Mendes, Rita P. Ribeiro, João Gama:
Fault Detection in Wastewater Treatment Plants: Application of Autoencoders Models with Streaming Data. PKDD/ECML Workshops (1) 2022: 55-70 - [c30]Nirbhaya Shaji, Thiago Andrade, Rita P. Ribeiro, João Gama:
Study on Correlation Between Vehicle Emissions and Air Quality in Porto. PKDD/ECML Workshops (1) 2022: 181-196 - [c29]Rita P. Ribeiro, Saulo Martiello Mastelini, Narjes Davari, Ehsan Aminian, Bruno Veloso, João Gama:
Online Anomaly Explanation: A Case Study on Predictive Maintenance. PKDD/ECML Workshops (2) 2022: 383-399 - [c28]Narjes Davari, Bruno Veloso, Rita P. Ribeiro, João Gama:
Fault Forecasting Using Data-Driven Modeling: A Case Study for Metro do Porto Data Set. PKDD/ECML Workshops (2) 2022: 400-409 - [c27]Emanuel Sousa Tomé, Rita P. Ribeiro, Bruno Veloso, João Gama:
An Online Data-Driven Predictive Maintenance Approach for Railway Switches. PKDD/ECML Workshops (2) 2022: 410-422 - [d2]Bruno Veloso, João Gama, Rita P. Ribeiro, Pedro Pereira:
MetroPT: A Benchmark dataset for predictive maintenance. Version 1. Zenodo, 2022 [all versions] - [d1]Bruno Veloso, João Gama, Rita P. Ribeiro, Pedro Pereira:
MetroPT2: A Benchmark dataset for predictive maintenance. Version V2. Zenodo, 2022 [all versions] - [i5]Anibal Silva, Rita P. Ribeiro, Nuno Moniz:
Model Optimization in Imbalanced Regression. CoRR abs/2206.09991 (2022) - [i4]Bruno Veloso, João Gama, Rita P. Ribeiro, Pedro Mota Pereira:
A Benchmark dataset for predictive maintenance. CoRR abs/2207.05466 (2022) - [i3]Sérgio M. Jesus, José Pombal, Duarte M. Alves, André Ferreira Cruz, Pedro Saleiro, Rita P. Ribeiro, João Gama, Pedro Bizarro:
Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation. CoRR abs/2211.13358 (2022) - 2021
- [j9]Ehsan Aminian, Rita P. Ribeiro, João Gama:
Chebyshev approaches for imbalanced data streams regression models. Data Min. Knowl. Discov. 35(6): 2389-2466 (2021) - [j8]Narjes Davari, Bruno Veloso, Gustavo de Assis Costa, Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
A Survey on Data-Driven Predictive Maintenance for the Railway Industry. Sensors 21(17): 5739 (2021) - [c26]João Gama, Bruno Veloso, Ehsan Aminian, Rita P. Ribeiro:
Current Trends in Learning from Data Streams. BDA 2021: 183-193 - [c25]Narjes Davari, Bruno Veloso, Rita P. Ribeiro, Pedro Mota Pereira, João Gama:
Predictive maintenance based on anomaly detection using deep learning for air production unit in the railway industry. DSAA 2021: 1-10 - [c24]Sónia Teixeira, Guilherme Londres, Bruno Veloso, Rita P. Ribeiro, João Gama:
Improving Smart Waste Collection Using AutoML. PKDD/ECML Workshops (2) 2021: 283-298 - [e6]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e5]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - 2020
- [j7]Rita P. Ribeiro, Nuno Moniz:
Imbalanced regression and extreme value prediction. Mach. Learn. 109(9-10): 1803-1835 (2020) - [c23]Pedro B. Vasconcelos, Rita P. Ribeiro:
Using Property-Based Testing to Generate Feedback for C Programming Exercises. ICPEC 2020: 28:1-28:10 - [c22]Mariana Barros, Bruno Veloso, Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
Failure Detection of an Air Production Unit in Operational Context. IoT Streams/ITEM@PKDD/ECML 2020: 61-74 - [e4]Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents]
2010 – 2019
- 2019
- [j6]Eduarda Portela, Rita P. Ribeiro, João Gama:
The search of conditional outliers. Intell. Data Anal. 23(1): 23-39 (2019) - [j5]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Pre-processing approaches for imbalanced distributions in regression. Neurocomputing 343: 76-99 (2019) - [c21]Ehsan Aminian, Rita P. Ribeiro, João Gama:
A Study on Imbalanced Data Streams. PKDD/ECML Workshops (2) 2019: 380-389 - [e3]Anna Monreale, Carlos Alzate, Michael Kamp, Yamuna Krishnamurthy, Daniel Paurat, Moamar Sayed Mouchaweh, Albert Bifet, João Gama, Rita P. Ribeiro:
ECML PKDD 2018 Workshops - DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers. Communications in Computer and Information Science 967, Springer 2019, ISBN 978-3-030-14879-9 [contents] - 2018
- [j4]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Resampling with neighbourhood bias on imbalanced domains. Expert Syst. J. Knowl. Eng. 35(4) (2018) - [c20]Paula Branco, Luís Torgo, Rita P. Ribeiro:
MetaUtil: Meta Learning for Utility Maximization in Regression. DS 2018: 129-143 - [c19]Nuno Moniz, Rita P. Ribeiro, Vítor Cerqueira, Nitesh V. Chawla:
SMOTEBoost for Regression: Improving the Prediction of Extreme Values. DSAA 2018: 150-159 - [c18]Paula Branco, Luís Torgo, Rita P. Ribeiro:
REBAGG: REsampled BAGGing for Imbalanced Regression. LIDTA@ECML/PKDD 2018: 67-81 - [e2]Moamar Sayed Mouchaweh, Hamid Bouchachia, João Gama, Rita Paula Ribeiro:
Proceedings of the Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV 2016) co-located with the 2016 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2016), Riva del Garda, Italy, September 23, 2016. CEUR Workshop Proceedings 2069, CEUR-WS.org 2018 [contents] - 2017
- [c17]Paula Branco, Luís Torgo, Rita P. Ribeiro, Eibe Frank, Bernhard Pfahringer, Markus Michael Rau:
Learning Through Utility Optimization in Regression Tasks. DSAA 2017: 30-39 - [c16]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems. EPIA 2017: 513-524 - [c15]Eduarda Portela, Rita P. Ribeiro, João Gama:
Outliers and the Simpson's Paradox. MICAI (1) 2017: 267-278 - [c14]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Relevance-Based Evaluation Metrics for Multi-class Imbalanced Domains. PAKDD (1) 2017: 698-710 - [c13]Paula Branco, Luís Torgo, Rita P. Ribeiro:
SMOGN: a Pre-processing Approach for Imbalanced Regression. LIDTA@PKDD/ECML 2017: 36-50 - [e1]Moamar Sayed Mouchaweh, Albert Bifet, Hamid Bouchachia, João Gama, Rita Paula Ribeiro:
Proceedings of the Workshop on IoT Large Scale Learning from Data Streams co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18-22, 2017. CEUR Workshop Proceedings 1958, CEUR-WS.org 2017 [contents] - 2016
- [j3]Paula Branco, Luís Torgo, Rita P. Ribeiro:
A Survey of Predictive Modeling on Imbalanced Domains. ACM Comput. Surv. 49(2): 31:1-31:50 (2016) - [j2]Rita P. Ribeiro, Pedro Mota Pereira, João Gama:
Sequential anomalies: a study in the Railway Industry. Mach. Learn. 105(1): 127-153 (2016) - [c12]Rita P. Ribeiro, Ricardo Oliveira, João Gama:
Detection of Fraud Symptoms in the Retail Industry. IBERAMIA 2016: 189-200 - [i2]Paula Branco, Rita P. Ribeiro, Luís Torgo:
UBL: an R package for Utility-based Learning. CoRR abs/1604.08079 (2016) - 2015
- [j1]Luís Torgo, Paula Branco, Rita P. Ribeiro, Bernhard Pfahringer:
Resampling strategies for regression. Expert Syst. J. Knowl. Eng. 32(3): 465-476 (2015) - [c11]Ana M. Silva, Rita P. Ribeiro, João Gama:
An Experimental Study on Predictive Models Using Hierarchical Time Series. EPIA 2015: 501-512 - [i1]Paula Branco, Luís Torgo, Rita P. Ribeiro:
A Survey of Predictive Modelling under Imbalanced Distributions. CoRR abs/1505.01658 (2015) - 2014
- [c10]Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
Failure Prediction - An Application in the Railway Industry. Discovery Science 2014: 264-275 - 2013
- [c9]Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, Paula Branco:
SMOTE for Regression. EPIA 2013: 378-389 - 2012
- [c8]Rita P. Ribeiro:
Towards Utility Maximization in Regression. ICDM Workshops 2012: 179-186 - 2010
- [c7]Orlando Ohashi, Luís Torgo, Rita P. Ribeiro:
Interval Forecast of Water Quality Parameters. ECAI 2010: 283-288
2000 – 2009
- 2009
- [c6]Luís Torgo, Rita P. Ribeiro:
Precision and Recall for Regression. Discovery Science 2009: 332-346 - 2007
- [c5]Luís Torgo, Rita P. Ribeiro:
Utility-Based Regression. PKDD 2007: 597-604 - 2006
- [c4]Rita P. Ribeiro, Luís Torgo:
Rule-Based Prediction of Rare Extreme Values. Discovery Science 2006: 219-230 - [c3]Luís Torgo, Rita P. Ribeiro:
Predicting Rare Extreme Values. PAKDD 2006: 816-820 - 2003
- [c2]Rita P. Ribeiro, Luís Torgo:
Predicting Harmful Algae Blooms. EPIA 2003: 308-312 - [c1]Luís Torgo, Rita P. Ribeiro:
Predicting Outliers. PKDD 2003: 447-458
Coauthor Index
João Gama 0001
aka: João Manuel Portela da Gama
aka: João Manuel Portela da Gama
[i11] [j12] [c51] [c50] [c49] [c47] [c46] [c44] [c43] [i10] [i9] [i8] [i7] [c42] [c41] [c40] [c39] [c38] [c37] [e9] [e8] [e7] [d3] [i6] [j10] [c35] [c34] [c32] [c31] [c30] [c29] [c28] [c27] [d2] [d1] [i4] [i3] [j9] [j8] [c26] [c25] [c24] [e6] [e5] [c22] [e4] [j6] [c21] [e3] [e2] [c15] [e1] [j2] [c12] [c11] [c10]
Bruno M. Veloso
aka: Bruno Veloso
aka: Bruno Veloso
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