Rita P. Ribeiro

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 50

Top Topics

Fault Detection

Class Imbalanced

Top Venues

PKDD/ECML Workshops (2)

Publications

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 (2024)
Matías Molina, Rita P. Ribeiro, Bruno Veloso, João Gama
Super-Resolution Analysis for Landfill Waste Classification. IDA (1) (2024)
César Andrade, Rita P. Ribeiro, João Gama
Community-Based Topic Modeling with Contextual Outlier Handling. CAEPIA (2024)
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 (2024)
Matías Molina, Rita P. Ribeiro, Bruno Veloso, João Gama
Super-Resolution Analysis for Landfill Waste Classification. CoRR (2024)
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 (2024)
João Gama, Slawomir Nowaczyk, Sepideh Pashami, Rita P. Ribeiro, Grzegorz J. Nalepa, Bruno Veloso
XAI for Predictive Maintenance. KDD (2023)
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)
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) (2023)
César Andrade, Rita P. Ribeiro, João Gama
Topic Model with Contextual Outlier Handling: a Study on Electronic Invoice Product Descriptions. EPIA (1) (2023)
Thiago Andrade, Nirbhaya Shaji, Rita P. Ribeiro, João Gama
Pollution Emission Patterns of Transportation in Porto, Portugal Through Network Analysis. EPIA (1) (2023)
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 (2023)
Sérgio M. Jesus, José Pombal, Duarte 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 (2022)
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)
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)
Bruno Veloso, João Gama, Rita P. Ribeiro, Pedro Mota Pereira
A Benchmark dataset for predictive maintenance. CoRR (2022)
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)
João Gama, Rita P. Ribeiro, Bruno Veloso
Data-Driven Predictive Maintenance. IEEE Intell. Syst. 37 (4) (2022)
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)
Anibal Silva, Rita P. Ribeiro, Nuno Moniz
Model Optimization in Imbalanced Regression. CoRR (2022)
Sérgio M. Jesus, José Pombal, Duarte 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)
Anibal Silva, Rita P. Ribeiro, Nuno Moniz
Model Optimization in Imbalanced Regression. DS (2022)
Nádia Soares, João F. Gonçalves, Raquel Vasconcelos, Rita P. Ribeiro
Combining Multiple Data Sources to Predict IUCN Conservation Status of Reptiles. IDA (2022)
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)
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)
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)
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) (2021)
Ehsan Aminian, Rita P. Ribeiro, João Gama
Chebyshev approaches for imbalanced data streams regression models. Data Min. Knowl. Discov. 35 (6) (2021)
João Gama, Bruno Veloso, Ehsan Aminian, Rita P. Ribeiro
Current Trends in Learning from Data Streams. BDA (2021)
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)
Sónia Teixeira, Guilherme Londres, Bruno Veloso, Rita P. Ribeiro, João Gama
Improving Smart Waste Collection Using AutoML. PKDD/ECML Workshops (2) (2021)
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)
Rita P. Ribeiro, Nuno Moniz
Imbalanced regression and extreme value prediction. Mach. Learn. 109 (9-10) (2020)
Pedro B. Vasconcelos, Rita P. Ribeiro
Using Property-Based Testing to Generate Feedback for C Programming Exercises. ICPEC (2020)
Ehsan Aminian, Rita P. Ribeiro, João Gama
A Study on Imbalanced Data Streams. PKDD/ECML Workshops (2) (2019)
Eduarda Portela, Rita P. Ribeiro, João Gama
The search of conditional outliers. Intell. Data Anal. 23 (1) (2019)
Paula Branco, Luís Torgo, Rita P. Ribeiro
Pre-processing approaches for imbalanced distributions in regression. Neurocomputing 343 (2019)
Paula Branco, Luís Torgo, Rita P. Ribeiro
MetaUtil: Meta Learning for Utility Maximization in Regression. DS (2018)
Paula Branco, Luís Torgo, Rita P. Ribeiro
REBAGG: REsampled BAGGing for Imbalanced Regression. LIDTA@ECML/PKDD (2018)
Paula Branco, Luís Torgo, Rita P. Ribeiro
Resampling with neighbourhood bias on imbalanced domains. Expert Syst. J. Knowl. Eng. 35 (4) (2018)
Nuno Moniz, Rita P. Ribeiro, Vítor Cerqueira, Nitesh V. Chawla
SMOTEBoost for Regression: Improving the Prediction of Extreme Values. DSAA (2018)
Paula Branco, Luís Torgo, Rita P. Ribeiro, Eibe Frank, Bernhard Pfahringer, Markus Michael Rau
Learning Through Utility Optimization in Regression Tasks. DSAA (2017)
Paula Branco, Luís Torgo, Rita P. Ribeiro
Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems. EPIA (2017)
Paula Branco, Luís Torgo, Rita P. Ribeiro
Relevance-Based Evaluation Metrics for Multi-class Imbalanced Domains. PAKDD (1) (2017)
Paula Branco, Luís Torgo, Rita P. Ribeiro
SMOGN: a Pre-processing Approach for Imbalanced Regression. LIDTA@PKDD/ECML (2017)
Eduarda Portela, Rita P. Ribeiro, João Gama
Outliers and the Simpson's Paradox. MICAI (1) (2017)
Paula Branco, Rita P. Ribeiro, Luís Torgo
UBL: an R package for Utility-based Learning. CoRR (2016)
Paula Branco, Luís Torgo, Rita P. Ribeiro
A Survey of Predictive Modeling on Imbalanced Domains. ACM Comput. Surv. 49 (2) (2016)
Rita P. Ribeiro, Pedro Mota Pereira, João Gama
Sequential anomalies: a study in the Railway Industry. Mach. Learn. 105 (1) (2016)
Rita P. Ribeiro, Ricardo Oliveira, João Gama
Detection of Fraud Symptoms in the Retail Industry. IBERAMIA (2016)
Paula Branco, Luís Torgo, Rita P. Ribeiro
A Survey of Predictive Modelling under Imbalanced Distributions. CoRR (2015)
Ana M. Silva, Rita P. Ribeiro, João Gama
An Experimental Study on Predictive Models Using Hierarchical Time Series. EPIA (2015)
Luís Torgo, Paula Branco, Rita P. Ribeiro, Bernhard Pfahringer
Resampling strategies for regression. Expert Syst. J. Knowl. Eng. 32 (3) (2015)
Pedro Mota Pereira, Rita P. Ribeiro, João Gama
Failure Prediction - An Application in the Railway Industry. Discovery Science (2014)
Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, Paula Branco
SMOTE for Regression. EPIA (2013)
Rita P. Ribeiro
Towards Utility Maximization in Regression. ICDM Workshops (2012)
Orlando Ohashi, Luís Torgo, Rita P. Ribeiro
Interval Forecast of Water Quality Parameters. ECAI (2010)
Luís Torgo, Rita P. Ribeiro
Precision and Recall for Regression. Discovery Science (2009)
Luís Torgo, Rita P. Ribeiro
Utility-Based Regression. PKDD (2007)
Luís Torgo, Rita P. Ribeiro
Predicting Rare Extreme Values. PAKDD (2006)
Rita P. Ribeiro, Luís Torgo
Rule-Based Prediction of Rare Extreme Values. Discovery Science (2006)
Rita P. Ribeiro, Luís Torgo
Predicting Harmful Algae Blooms. EPIA (2003)
Luís Torgo, Rita P. Ribeiro
Predicting Outliers. PKDD (2003)