Panel: Learning in Distributed Systems and Multi-Agent Environments. - Pavel Brazdil; Matjaz Gams; Sati S. Sian; Luís Torgo; Walter Van de Velde (EWSL, 1991)

Controlled Redundancy in Incremental Rule Learning. - Luís Torgo (ECML, 1993)

Rule Combination in Inductive Learning. - Luís Torgo (ECML, 1993)

Regression by Classification. - Luís Torgo; João Gama 001 (SBIA, 1996)

Search-Based Class Discretization. - Luís Torgo; João Gama 001 (ECML, 1997)

Functional Models for Regression Tree Leaves. - Luís Torgo (ICML, 1997)

Regression Using Classification Algorithms. - Luís Torgo; João Gama 001 (Intell. Data Anal., 1997)

Error Estimators for Pruning Regression Trees. - Luís Torgo (ECML, 1998)

Dynamic Discretization of Continuous Attributes. - João Gama 001; Luís Torgo; Carlos Soares (IBERAMIA, 1998)

Partial Linear Trees. - Luís Torgo (ICML, 2000)

Efficient and Comprehensible Local Regression. - Luís Torgo (PAKDD, 2000)

Thesis: Inductive learning to tree-based regression models. - Luís Torgo (AI Commun., 2000)

The Use of Domain Knowledge in Feature Construction for Financial Time Series Prediction. - Pedro de Almeida; Luís Torgo (EPIA, 2001)

A Study on End-Cut Preference in Least Squares Regression Trees. - Luís Torgo (EPIA, 2001)

Predicting Harmful Algae Blooms. - Rita P. Ribeiro; Luís Torgo (EPIA, 2003)

Automatic Selection of Table Areas in Documents for Information Extraction. - Ana Costa e Silva; Alípio Jorge; Luís Torgo (EPIA, 2003)

Predicting Outliers. - Luís Torgo; Rita P. Ribeiro (PKDD, 2003)

Clustered Partial Linear Regression. - Luís Torgo; Joaquim Pinto da Costa (Mach. Learn., 2003)

Adapting Peepholing to Regression Trees. - Luís Torgo; Joana Marques (EPIA, 2005)

Regression error characteristic surfaces. - Luís Torgo (KDD, 2005)

Rule-Based Prediction of Rare Extreme Values. - Rita P. Ribeiro; Luís Torgo (Discovery Science, 2006)

Predicting Rare Extreme Values. - Luís Torgo; Rita P. Ribeiro (PAKDD, 2006)

Design of an end-to-end method to extract information from tables. - Ana Costa e Silva; Alípio Mário Jorge; Luís Torgo (Int. J. Document Anal. Recognit., 2006)

Resource-Bounded Fraud Detection. - Luís Torgo (EPIA Workshops, 2007)

Utility-Based Regression. - Luís Torgo; Rita P. Ribeiro (PKDD, 2007)

Precision and Recall for Regression. - Luís Torgo; Rita P. Ribeiro (Discovery Science, 2009)

Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data. - Luís Torgo; Welma Pereira; Carlos Soares (EPIA, 2009)

Data Mining with R: Learning with Case Studies - Luís Torgo (Chapman and Hall/CRC Press, 2010)

Interval Forecast of Water Quality Parameters. - Orlando Ohashi; Luís Torgo; Rita P. Ribeiro (ECAI, 2010)

Model Trees. - Luís Torgo (Encyclopedia of Machine Learning, 2010)

Regression Trees. - Luís Torgo (Encyclopedia of Machine Learning, 2010)

Resource-bounded Outlier Detection using Clustering Methods. - Luís Torgo; Carlos Soares (Data Mining for Business Applications, 2010)

Utility-Based Fraud Detection. - Luís Torgo; Elsa Lopes (IJCAI, 2011)

2D-interval predictions for time series. - Luís Torgo; Orlando Ohashi (KDD, 2011)

A Contextual Classification Strategy for Polarity Analysis of Direct Quotations from Financial News. - Brett Drury; Gaël Dias; Luís Torgo (RANLP, 2011)

Wind speed forecasting using spatio-temporal indicators. - Orlando Ohashi; Luís Torgo (ECAI, 2012)

Spatial Interpolation Using Multiple Regression. - Orlando Ohashi; Luís Torgo (ICDM, 2012)

Classifying News Stories with a Constrained Learning Strategy to Estimate the Direction of a Market Index. - Brett Drury; Luís Torgo; José João Almeida (Int. J. Comput. Sci. Appl., 2012)

SMOTE for Regression. - Luís Torgo; Rita P. Ribeiro; Bernhard Pfahringer; Paula Branco (EPIA, 2013)

OpenML: A Collaborative Science Platform. - Jan N. van Rijn; Bernd Bischl; Luís Torgo; Bo Gao 002; Venkatesh Umaashankar; Simon Fischer 001; Patrick Winter; Bernd Wiswedel; Michael R. Berthold; Joaquin Vanschoren (ECML/PKDD (3), 2013)

OpenML: networked science in machine learning. - Joaquin Vanschoren; Jan N. van Rijn; Bernd Bischl; Luís Torgo (SIGKDD Explor., 2013)

Ensembles for Time Series Forecasting. - Mariana Oliveira 001; Luís Torgo (ACML, 2014)

Resampling Approaches to Improve News Importance Prediction. - Nuno Moniz; Luís Torgo; Fátima Rodrigues 001 (IDA, 2014)

An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R. - Luís Torgo (CoRR, 2014)

Forecasting the Correct Trading Actions. - Luís Baía; Luís Torgo (EPIA, 2015)

Class-Based Outlier Detection: Staying Zombies or Awaiting for Resurrection? - Leona Nezvalová; Lubos Popelínský; Luís Torgo; Karel Vaculík (IDA, 2015)

A Survey of Predictive Modelling under Imbalanced Distributions. - Paula Branco; Luís Torgo; Rita P. Ribeiro (CoRR, 2015)

Socially Driven News Recommendation. - Nuno Moniz; Luís Torgo (CoRR, 2015)

Resampling strategies for regression. - Luís Torgo; Paula Branco; Rita P. Ribeiro; Bernhard Pfahringer (Expert Syst. J. Knowl. Eng., 2015)

Predicting Wildfires - Propositional and Relational Spatio-Temporal Pre-processing Approaches. - Mariana Oliveira 001; Luís Torgo; Vítor Santos Costa (DS, 2016)

Resampling Strategies for Imbalanced Time Series. - Nuno Moniz; Paula Branco; Luís Torgo (DSAA, 2016)

Lexicon Expansion System for Domain and Time Oriented Sentiment Analysis. - Nuno Guimarães; Luís Torgo; Álvaro Figueira (KDIR, 2016)

Time-Based Ensembles for Prediction of Rare Events in News Stream. - Nuno Moniz; Luís Torgo; Magdalini Eirinaki (ICDM Workshops, 2016)

UBL: an R package for Utility-based Learning. - Paula Branco; Rita P. Ribeiro; Luís Torgo (CoRR, 2016)

Data-Driven Relevance Judgments for Ranking Evaluation. - Nuno Moniz; Luís Torgo; João Vinagre (CoRR, 2016)

A Survey of Predictive Modeling on Imbalanced Domains. - Paula Branco; Luís Torgo; Rita P. Ribeiro (ACM Comput. Surv., 2016)

Learning Through Utility Optimization in Regression Tasks. - Paula Branco; Luís Torgo; Rita P. Ribeiro; Eibe Frank; Bernhard Pfahringer; Markus Michael Rau (DSAA, 2017)

Dynamic and Heterogeneous Ensembles for Time Series Forecasting. - Vítor Cerqueira; Luís Torgo; Mariana Oliveira 001; Bernhard Pfahringer (DSAA, 2017)

A Comparative Study of Performance Estimation Methods for Time Series Forecasting. - Vítor Cerqueira; Luís Torgo; Jasmina Smailovic; Igor Mozetic (DSAA, 2017)

Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems. - Paula Branco; Luís Torgo; Rita P. Ribeiro (EPIA, 2017)

Arbitrated Ensemble for Solar Radiation Forecasting. - Vítor Cerqueira; Luís Torgo; Carlos Soares (IWANN (1), 2017)

Relevance-Based Evaluation Metrics for Multi-class Imbalanced Domains. - Paula Branco; Luís Torgo; Rita P. Ribeiro (PAKDD (1), 2017)

SMOGN: a Pre-processing Approach for Imbalanced Regression. - Paula Branco; Luís Torgo; Rita P. Ribeiro (LIDTA@PKDD/ECML, 2017)

Arbitrated Ensemble for Time Series Forecasting. - Vítor Cerqueira; Luís Torgo; Fábio Pinto; Carlos Soares (ECML/PKDD (2), 2017)

Evaluation of Ensemble Methods in Imbalanced Regression Tasks. - Nuno Moniz; Paula Branco; Luís Torgo (LIDTA@PKDD/ECML, 2017)

Learning with Imbalanced Domains: Preface. - Luís Torgo; Bartosz Krawczyk; Paula Branco; Nuno Moniz (LIDTA@PKDD/ECML, 2017)

A comparative study of approaches to forecast the correct trading actions. - Luís Baía; Luís Torgo (Expert Syst. J. Knowl. Eng., 2017)

Resampling strategies for imbalanced time series forecasting. - Nuno Moniz; Paula Branco; Luís Torgo (Int. J. Data Sci. Anal., 2017)

A Framework for Recommendation of Highly Popular News Lacking Social Feedback. - Nuno Moniz; Luís Torgo; Magdalini Eirinaki; Paula Branco (New Gener. Comput., 2017)

Model Trees. - Luís Torgo (Encyclopedia of Machine Learning and Data Mining, 2017)

Regression Trees. - Luís Torgo (Encyclopedia of Machine Learning and Data Mining, 2017)

MetaUtil: Meta Learning for Utility Maximization in Regression. - Paula Branco; Luís Torgo; Rita P. Ribeiro (DS, 2018)

The Utility Problem of Web Content Popularity Prediction. - Nuno Moniz; Luís Torgo (HT, 2018)

Contributions to the Detection of Unreliable Twitter Accounts through Analysis of Content and Behaviour. - Nuno Guimarães; Álvaro Figueira; Luís Torgo (KDIR, 2018)

Analysis and Detection of Unreliable Users in Twitter: Two Case Studies. - Nuno Guimarães; Álvaro Figueira; Luís Torgo (IC3K, 2018)

Evaluation Procedures for Forecasting with Spatio-Temporal Data. - Mariana Oliveira 001; Luís Torgo; Vítor Santos Costa (ECML/PKDD (1), 2018)

REBAGG: REsampled BAGGing for Imbalanced Regression. - Paula Branco; Luís Torgo; Rita P. Ribeiro (LIDTA@ECML/PKDD, 2018)

Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles. - Vítor Cerqueira; Fábio Pinto; Luís Torgo; Carlos Soares; Nuno Moniz (ECML/PKDD (1), 2018)

2nd Workshop on Learning with Imbalanced Domains: Preface. - Luís Torgo; Stan Matwin; Nathalie Japkowicz; Bartosz Krawczyk; Nuno Moniz; Paula Branco (LIDTA@ECML/PKDD, 2018)

Cost-Sensitive Learning: Preface. - Luís Torgo; Stan Matwin; Gary Weiss 001; Nuno Moniz; Paula Branco (COST@SDM, 2018)

Current State of the Art to Detect Fake News in Social Media: Global Trendings and Next Challenges. - Álvaro Figueira; Nuno Guimarães; Luís Torgo (WEBIST, 2018)

Multi-Source Social Feedback of Online News Feeds. - Nuno Moniz; Luís Torgo (CoRR, 2018)

How to evaluate sentiment classifiers for Twitter time-ordered data? - Igor Mozetic; Luís Torgo; Vítor Cerqueira; Jasmina Smailovic (CoRR, 2018)

Resampling with neighbourhood bias on imbalanced domains. - Paula Branco; Luís Torgo; Rita P. Ribeiro (Expert Syst. J. Knowl. Eng., 2018)

Twitter as a Source for Time- and Domain-Dependent Sentiment Lexicons. - Nuno Guimarães; Luís Torgo; Álvaro Figueira (Social Network Based Big Data Analysis and Applications, 2018)

News Popularity in Multiple Social Media Platforms. - Luís Torgo; Nuno Moniz (UCI Machine Learning Repository, 2018)

The CURE for Class Imbalance. - Colin Bellinger; Paula Branco; Luís Torgo (DS, 2019)

Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. - Vítor Cerqueira; Luís Torgo; Carlos Soares (DS, 2019)

Explaining the Performance of Black Box Regression Models. - Inês Areosa; Luís Torgo (DSAA, 2019)

A Study on the Impact of Data Characteristics in Imbalanced Regression Tasks. - Paula Branco; Luís Torgo (DSAA, 2019)

On Feature Selection and Evaluation of Transportation Mode Prediction Strategies. - Mohammad Etemad; Amílcar Soares Júnior 001; Stan Matwin; Luís Torgo (EDBT/ICDT Workshops, 2019)

Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters. - Vítor Cerqueira; Luís Torgo; Carlos Soares (CoRR, 2019)

Pre-processing approaches for imbalanced distributions in regression. - Paula Branco; Luís Torgo; Rita P. Ribeiro (Neurocomputing, 2019)

A Brief Overview on the Strategiesto Fight Back the Spreadof False Information. - Álvaro Figueira; Nuno Guimarães; Luís Torgo (J. Web Eng., 2019)

Arbitrage of forecasting experts. - Vítor Cerqueira; Luís Torgo; Fábio Pinto; Carlos Soares (Mach. Learn., 2019)

A review on web content popularity prediction: Issues and open challenges. - Nuno Moniz; Luís Torgo (Online Soc. Networks Media, 2019)

Wise Sliding Window Segmentation: A Classification-Aided Approach for Trajectory Segmentation. - Mohammad Etemad; Zahra Etemad; Amílcar Soares Júnior 001; Vania Bogorny; Stan Matwin; Luís Torgo (Canadian AI, 2020)

Knowledge-based Reliability Metrics for Social Media Accounts. - Nuno Guimarães; Álvaro Figueira; Luís Torgo (WEBIST, 2020)

Visual interpretation of regression error. - Inês Areosa; Luís Torgo (Expert Syst. J. Knowl. Eng., 2020)

Evaluating time series forecasting models: an empirical study on performance estimation methods. - Vítor Cerqueira; Luís Torgo; Igor Mozetic (Mach. Learn., 2020)

Active Learning for Imbalanced Domains: the ALOD and ALOD-RE Algorithms. - Mayukh Bhattacharjee; Hema Sri Kambhampati; Paula Branco; Luís Torgo (DSAA, 2021)

3rd Workshop on Learning with Imbalanced Domains: Preface. - Nuno Moniz; Paula Branco; Luís Torgo; Nathalie Japkowicz; Michal Wozniak 001; Shuo Wang (LIDTA@ECML/PKDD, 2021)

An organized review of key factors for fake news detection. - Nuno Guimarães; Álvaro Figueira; Luís Torgo (CoRR, 2021)

Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators. - Vítor Cerqueira; Luís Torgo; Carlos Soares (CoRR, 2021)

Model Compression for Dynamic Forecast Combination. - Vítor Cerqueira; Luís Torgo; Carlos Soares; Albert Bifet (CoRR, 2021)

Beyond Average Performance - exploring regions of deviating performance for black box classification models. - Luís Torgo; Paulo Azevedo; Inês Areosa (CoRR, 2021)

SWS: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels. - Mohammad Etemad; Amílcar Soares Júnior 001; Elham Etemad; Jordan Rose; Luís Torgo; Stan Matwin (GeoInformatica, 2021)

Biased resampling strategies for imbalanced spatio-temporal forecasting. - Mariana Oliveira 001; Nuno Moniz; Luís Torgo; Vítor Santos Costa (Int. J. Data Sci. Anal., 2021)

Towards a pragmatic detection of unreliable accounts on social networks. - Nuno Guimarães; Álvaro Figueira; Luís Torgo (Online Soc. Networks Media, 2021)

A Clustering-based Approach for Predicting the Future Location of a Vessel. - Md. Mahbub Alam; Luís Torgo (Canadian AI, 2022)

4th Workshop on Learning with Imbalanced Domains: Preface. - Nuno Moniz; Paula Branco; Luís Torgo; Nathalie Japkowicz; Michal Wozniak 001; Shuo Wang (LIDTA, 2022)

Exceedance Probability Forecasting via Regression for Significant Wave Height Forecasting. - Vítor Cerqueira; Luís Torgo (CoRR, 2022)

A case study comparing machine learning with statistical methods for time series forecasting: size matters. - Vítor Cerqueira; Luís Torgo; Carlos Soares (J. Intell. Inf. Syst., 2022)

A Survey on Spatio-temporal Data Analytics Systems. - Md. Mahbub Alam; Luís Torgo; Albert Bifet (ACM Comput. Surv., 2022)

Multi-output Ensembles for Multi-step Forecasting. - Vítor Cerqueira; Luís Torgo (CoRR, 2023)

Subgroup mining for performance analysis of regression models. - João Pimentel 003; Paulo J. Azevedo; Luís Torgo (Expert Syst. J. Knowl. Eng., 2023)

Automated imbalanced classification via layered learning. - Vítor Cerqueira; Luís Torgo; Paula Branco; Colin Bellinger (Mach. Learn., 2023)

STUDD: a student-teacher method for unsupervised concept drift detection. - Vítor Cerqueira; Heitor Murilo Gomes; Albert Bifet; Luís Torgo (Mach. Learn., 2023)

Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes. - Vítor Cerqueira; Luís Torgo; Carlos Soares (Mach. Learn., 2023)

Model Selection for Time Series Forecasting An Empirical Analysis of Multiple Estimators. - Vítor Cerqueira; Luís Torgo; Carlos Soares (Neural Process. Lett., 2023)

RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. - Luis Roque; Carlos Soares; Luís Torgo (KDD, 2024)

Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine. - Luis Roque; Vítor Cerqueira; Carlos Soares; Luís Torgo (AAAI, 2025)

Architecture and implementation of ulrb algorithm in R. - Francisco Pascoal; Rodrigo Costa; Luís Torgo; Catarina Magalhães; Paula Branco (Ecol. Informatics, 2025)

L-GTA: Latent Generative Modeling for Time Series Augmentation. - Luis Roque; Carlos Soares; Vítor Cerqueira; Luís Torgo (CoRR, 2025)