POPSTAR at RepLab 2013: Name Ambiguity Resolution on Twitter. - Pedro Saleiro; Luis Rei; Arian Pasquali; Carlos Soares; Jorge Teixeira; Fábio Pinto; Mohammad Nozari Zarmehri; Catarina Félix; Pedro Strecht (CLEF (Working Notes), 2013)

"Piaf" vs "Adele": classifying encyclopedic queries using automatically labeled training data. - Pedro Saleiro; Luís Sarmento (OAIR, 2013)

POPmine: Tracking Political Opinion on the Web. - Pedro Saleiro; Silvio Amir; Mário J. Silva; Carlos Soares (CIT/IUCC/DASC/PICom, 2015)

SentiBubbles: Topic Modeling and Sentiment Visualization of Entity-centric Tweets. - João Oliveira; Mike Pinto; Pedro Saleiro; Jorge Teixeira (C3S2E, 2016)

Sentiment Aggregate Functions for Political Opinion Polling using Microblog Streams. - Pedro Saleiro; Luís Gomes; Carlos Soares (C3S2E, 2016)

TimeMachine: Entity-Centric Search and Visualization of News Archives. - Pedro Saleiro; Jorge Teixeira; Carlos Soares; Eugénio C. Oliveira (ECIR, 2016)

Learning from the News: Predicting Entity Popularity on Twitter. - Pedro Saleiro; Carlos Soares (IDA, 2016)

Mining social media for open innovation in transportation systems. - Daniela Ulloa; Pedro Saleiro; Rosaldo J. F. Rossetti; Elis Regina Silva (ITSC, 2016)

Transportation in Social Media: An Automatic Classifier for Travel-Related Tweets. - João Pereira 005; Arian Pasquali; Pedro Saleiro; Rosaldo Rossetti (EPIA, 2017)

Learning Word Embeddings from the Portuguese Twitter Stream: A Study of Some Practical Aspects. - Pedro Saleiro; Luís Sarmento; Eduarda Mendes Rodrigues; Carlos Soares; Eugénio C. Oliveira (EPIA, 2017)

FEUP at SemEval-2017 Task 5: Predicting Sentiment Polarity and Intensity with Financial Word Embeddings. - Pedro Saleiro; Eduarda Mendes Rodrigues; Carlos Soares; Eugénio C. Oliveira (SemEval@ACL, 2017)

RELink: A Research Framework and Test Collection for Entity-Relationship Retrieval. - Pedro Saleiro; Natasa Milic-Frayling; Eduarda Mendes Rodrigues; Carlos Soares (SIGIR, 2017)

Early Fusion Strategy for Entity-Relationship Retrieval. - Pedro Saleiro; Natasa Milic-Frayling; Eduarda Mendes Rodrigues; Carlos Soares (KG4IR@SIGIR, 2017)

Characterizing Geo-located Tweets in Brazilian Megacities. - João Pereira 005; Arian Pasquali; Pedro Saleiro; Rosaldo Rossetti; Nélio Cacho (CoRR, 2017)

TexRep: A Text Mining Framework for Online Reputation Monitoring. - Pedro Saleiro; Eduarda Mendes Rodrigues; Carlos Soares; Eugénio Oliveira (New Gener. Comput., 2017)

Social Media Brand Engagement as a Proxy for E-Commerce Activities: A Case Study of Sina Weibo and JD. - Weiqiang Lin; Pedro Saleiro; Natasa Milic-Frayling; Eugene Ch'ng (WI, 2018)

Entity Retrieval and Text Mining for Online Reputation Monitoring. - Pedro Saleiro (CoRR, 2018)

Entity-Relationship Search over the Web. - Pedro Saleiro; Natasa Milic-Frayling; Eduarda Mendes Rodrigues; Carlos Soares (CoRR, 2018)

Aequitas: A Bias and Fairness Audit Toolkit. - Pedro Saleiro; Benedict Kuester; Abby Stevens; Ari Anisfeld; Loren Hinkson; Jesse London; Rayid Ghani (CoRR, 2018)

Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial. - Pedro Saleiro; Kit T. Rodolfa; Rayid Ghani (KDD, 2020)

A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization. - André Ferreira Cruz; Pedro Saleiro; Catarina G. Belém; Carlos Soares; Pedro Bizarro (CoRR, 2020)

Teaching the Machine to Explain Itself using Domain Knowledge. - Vladimir Balayan; Pedro Saleiro; Catarina G. Belém; Ludwig Krippahl; Pedro Bizarro (CoRR, 2020)

How can I choose an explainer?: An Application-grounded Evaluation of Post-hoc Explanations. - Sérgio M. Jesus; Catarina G. Belém; Vladimir Balayan; João Bento 002; Pedro Saleiro; Pedro Bizarro; João Gama 001 (FAccT, 2021)

Promoting Fairness through Hyperparameter Optimization. - André Ferreira Cruz; Pedro Saleiro; Catarina G. Belém; Carlos Soares; Pedro Bizarro (ICDM, 2021)

TimeSHAP: Explaining Recurrent Models through Sequence Perturbations. - João Bento 002; Pedro Saleiro; André Ferreira Cruz; Mário A. T. Figueiredo; Pedro Bizarro (KDD, 2021)

Weakly Supervised Multi-task Learning for Concept-based Explainability. - Catarina G. Belém; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro (CoRR, 2021)

LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering. - Mário Cardoso; Pedro Saleiro; Pedro Bizarro (ICAIF, 2022)

Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation. - Sérgio M. Jesus; José Pombal; Duarte M. Alves; André Ferreira Cruz; Pedro Saleiro; Rita P. Ribeiro; João Gama 001; Pedro Bizarro (NeurIPS, 2022)

ConceptDistil: Model-Agnostic Distillation of Concept Explanations. - João Bento Sousa; Ricardo Moreira; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro (CoRR, 2022)

Prisoners of Their Own Devices: How Models Induce Data Bias in Performative Prediction. - José Pombal; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2022)

Human-AI Collaboration in Decision-Making: Beyond Learning to Defer. - Diogo Leitão; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2022)

Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions. - José Pombal; André Ferreira Cruz; João Bravo; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2022)

FairGBM: Gradient Boosting with Fairness Constraints. - André Ferreira Cruz; Catarina G. Belém; João Bravo; Pedro Saleiro; Pedro Bizarro (ICLR, 2023)

Addressing Bias and Fairness in Machine Learning: A Practical Guide and Hands-on Tutorial. - Rayid Ghani; Kit T. Rodolfa; Pedro Saleiro; Sérgio M. Jesus (KDD, 2023)

A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies. - Ada Martin; Valerie Chen; Sérgio M. Jesus; Pedro Saleiro (CoRR, 2023)

Fairness-Aware Data Valuation for Supervised Learning. - José Pombal; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2023)

FiFAR: A Fraud Detection Dataset for Learning to Defer. - Jean V. Alves; Diogo Leitão; Sérgio M. Jesus; Marco O. P. Sampaio; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2023)

On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods. - Kasun Amarasinghe; Kit T. Rodolfa; Sérgio M. Jesus; Valerie Chen; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro; Ameet Talwalkar; Rayid Ghani (AAAI, 2024)

DiConStruct: Causal Concept-based Explanations through Black-Box Distillation. - Ricardo Miguel de Oliveira Moreira; Jacopo Bono; Mário Cardoso; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CLeaR, 2024)

Fair-OBNC: Correcting Label Noise for Fairer Datasets. - Inês Oliveira e Silva; Sérgio M. Jesus; Hugo M. Ferreira; Pedro Saleiro; Inês Sousa; Pedro Bizarro; Carlos Soares (ECAI, 2024)

Aequitas Flow: Streamlining Fair ML Experimentation. - Sérgio M. Jesus; Pedro Saleiro; Inês Oliveira e Silva; Beatriz M. Jorge; Rita P. Ribeiro; João Gama 001; Pedro Bizarro; Rayid Ghani (CoRR, 2024)

Mind the truncation gap: challenges of learning on dynamic graphs with recurrent architectures. - João Bravo; Jacopo Bono; Pedro Saleiro; Hugo M. Ferreira; Pedro Bizarro (CoRR, 2024)

Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints. - Jean V. Alves; Diogo Leitão; Sérgio M. Jesus; Marco O. P. Sampaio; Javier Liébana; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (Trans. Mach. Learn. Res., 2024)

Mind the truncation gap: challenges of learning on dynamic graphs with recurrent architectures. - João Bravo; Jacopo Bono; Hugo Ferreira 006; Pedro Saleiro; Pedro Bizarro (Trans. Mach. Learn. Res., 2024)