Extracting Structure, Text and Entities from PDF Documents of the Portuguese Legislation. - Nuno Moniz; Fátima Rodrigues 001 (KDIR, 2012)

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

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

Threshold-Bounded Influence Dominating Sets for Recommendations in Social Networks. - Magdalini Eirinaki; Nuno Moniz; Katerina Potika (BDCloud-SocialCom-SustainCom, 2016)

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

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

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

Relational Data on Members of Portuguese Governments (1976-2014). - Nuno Moniz; Adriano Campos (Data, 2016)

Empirical analysis of the Portuguese governments social network. - Nuno Moniz; Francisco Louçã; Márcia D. B. Oliveira; Renato Soeiro (Soc. Netw. Anal. Min., 2016)

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)

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)

Prediction and Ranking of Highly Popular Web Content - Nuno Moniz (2017)

SMOTEBoost for Regression: Improving the Prediction of Extreme Values. - Nuno Moniz; Rita P. Ribeiro; Vítor Cerqueira; Nitesh V. Chawla (DSAA, 2018)

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

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

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

Real-time 2019 Portuguese Parliament Election Results Dataset. - Nuno Moniz (CoRR, 2019)

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

Sequence Mining for Automatic Generation of Software Tests from GUI Event Traces. - Alberto Oliveira; Ricardo Freitas; Alípio Jorge; Vítor Amorim; Nuno Moniz; Ana C. R. Paiva; Paulo J. Azevedo (IDEAL (2), 2020)

Underground Train Tracking using Mobile Phone Accelerometer Data. - Yassine Baghoussi; João Mendes-Moreira 001; Nuno Moniz; Carlos Soares (ITSC, 2020)

Imbalanced regression and extreme value prediction. - Rita P. Ribeiro; Nuno Moniz (Mach. Learn., 2020)

The Compromise of Data Privacy in Predictive Performance. - Tânia Carvalho; Nuno Moniz (IDA, 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)

Automated imbalanced classification via meta-learning. - Nuno Moniz; Vítor Cerqueira (Expert Syst. Appl., 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)

No Free Lunch in imbalanced learning. - Nuno Moniz; Hugo Monteiro (Knowl. Based Syst., 2021)

Model Optimization in Imbalanced Regression. - Anibal Silva; Rita P. Ribeiro; Nuno Moniz (DS, 2022)

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

Survey on Privacy-Preserving Techniques for Data Publishing. - Tânia Carvalho; Nuno Moniz; Pedro Faria; Luís Antunes 002 (CoRR, 2022)

Privacy-Preserving Data Synthetisation for Secure Information Sharing. - Tânia Carvalho; Nuno Moniz; Pedro Faria; Luís Antunes 002; Nitesh V. Chawla (CoRR, 2022)

Robustness Evaluation of Regression Tasks with Skewed Domain Preferences. - Nuno Costa; Nuno Moniz (CoRR, 2022)

First Workshop on Machine Learning Challenges in Cybersecurity. - Paula Branco; Nuno Moniz; Guy-Vincent Jourdan (CASCON, 2023)

Fairness-Aware Mixture of Experts with Interpretability Budgets. - Joe Germino; Nuno Moniz; Nitesh V. Chawla (DS, 2023)

A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics. - Tânia Carvalho; Nuno Moniz; Luis Antunes 002 (EPIA (1), 2023)

Imbalanced Regression Evaluation Under Uncertain Domain Preferences. - Nuno Costa; Nuno Moniz (EPIA (1), 2023)

Experiential-Informed Data Reconstruction for Fishery Sustainability and Policies in the Azores. - Brenda Nogueira; Gui M. Menezes; Nuno Moniz (CoRR, 2023)

Survey on Privacy-Preserving Techniques for Microdata Publication. - Tânia Carvalho; Nuno Moniz; Pedro Faria; Luís Antunes 002 (ACM Comput. Surv., 2023)

Towards a data privacy-predictive performance trade-off. - Tânia Carvalho; Nuno Moniz; Pedro Faria; Luís Antunes 002 (Expert Syst. Appl., 2023)

Time Series Data Augmentation as an Imbalanced Learning Problem. - Vítor Cerqueira; Nuno Moniz; Ricardo Inácio; Carlos Soares (EPIA (2), 2024)

Dynamics of Fisheries in the Azores Islands: A Network Analysis Approach. - Brenda Nogueira; Ana Torres; Nuno Moniz; Gui M. Menezes (EPIA (2), 2024)

AnyLoss: Transforming Classification Metrics into Loss Functions. - Do Heon Han; Nuno Moniz; Nitesh V. Chawla (KDD, 2024)

Synthetic Data Outliers: Navigating Identity Disclosure. - Carolina Trindade; Luis Antunes 002; Tânia Carvalho; Nuno Moniz (PSD, 2024)

Are we Making Much Progress? Revisiting Chemical Reaction Yield Prediction from an Imbalanced Regression Perspective. - Yihong Ma; Xiaobao Huang; Bozhao Nan; Nuno Moniz; Xiangliang Zhang 001; Olaf Wiest; Nitesh V. Chawla (WWW (Companion Volume), 2024)

Conformalized Selective Regression. - Anna Sokol; Nuno Moniz; Nitesh V. Chawla (CoRR, 2024)

Fast Explainability via Feasible Concept Sets Generator. - Deng Pan; Nuno Moniz; Nitesh V. Chawla (CoRR, 2024)

Automated Privacy-Preserving Techniques via Meta-Learning. - Tânia Carvalho; Nuno Moniz; Luís Antunes 002 (CoRR, 2024)

Empowering Open Data Sharing for Social Good: A Privacy-Aware Approach. - Tânia Carvalho; Luís Antunes 002; Cristina Costa; Nuno Moniz (CoRR, 2024)

BenchmarkCards: Large Language Model and Risk Reporting. - Anna Sokol; Nuno Moniz; Elizabeth Daly; Michael Hind; Nitesh V. Chawla (CoRR, 2024)

LabSafety Bench: Benchmarking LLMs on Safety Issues in Scientific Labs. - Yujun Zhou 002; Jingdong Yang; Kehan Guo; Pin-Yu Chen; Tian Gao; Werner Geyer; Nuno Moniz; Nitesh V. Chawla; Xiangliang Zhang 001 (CoRR, 2024)

Class-Aware Contrastive Optimization for Imbalanced Text Classification. - Grigorii Khvatskii; Nuno Moniz; Khoa Doan; Nitesh V. Chawla (CoRR, 2024)

VEST: automatic feature engineering for forecasting. - Vítor Cerqueira; Nuno Moniz; Carlos Soares (Mach. Learn., 2024)

FairMOE: counterfactually-fair mixture of experts with levels of interpretability. - Joe Germino; Nuno Moniz; Nitesh V. Chawla (Mach. Learn., 2024)

NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning. - Zheyuan Zhang; Yiyang Li; Nhi Ha Lan Le; Zehong Wang; Tianyi Ma; Vincent Galassi; Keerthiram Murugesan; Nuno Moniz; Werner Geyer; Nitesh V. Chawla; Chuxu Zhang; Yanfang Ye 001 (ACL (1), 2025)

Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge. - Jiayi Ye; Yanbo Wang 005; Yue Huang 001; Dongping Chen; Qihui Zhang; Nuno Moniz; Tian Gao; Werner Geyer; Chao Huang 001; Pin-Yu Chen; Nitesh V. Chawla; Xiangliang Zhang 001 (ICLR, 2025)

Relevance-Aware Algorithmic Recourse. - Dongwhi Kim; Nuno Moniz (IDA, 2025)

Intersectional Divergence: Measuring Fairness in Regression. - Joe Germino; Nuno Moniz; Nitesh V. Chawla (CoRR, 2025)

Context Attribution with Multi-Armed Bandit Optimization. - Deng Pan; Keerthiram Murugesan; Nuno Moniz; Nitesh V. Chawla (CoRR, 2025)

Spectral Manifold Harmonization for Graph Imbalanced Regression. - Brenda Nogueira; Gabe Gomes; Meng Jiang 001; Nitesh V. Chawla; Nuno Moniz (CoRR, 2025)

Differentially-private data synthetisation for efficient re-identification risk control. - Tânia Carvalho; Nuno Moniz; Luis Antunes 002; Nitesh V. Chawla (Mach. Learn., 2025)

Class-Imbalanced Learning on Graphs: A Survey. - Yihong Ma; Yijun Tian 001; Nuno Moniz; Nitesh V. Chawla (ACM Comput. Surv., 2025)