PPaperPicks

Carlos Soares

University of Porto, Portugal

21 papers at tracked venues · 3 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IX
  2. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track and Demo Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part X
  3. Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part I
  4. Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part II
  5. Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part III
  6. Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part IV
  7. Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part V
  8. Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VI
  9. Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VII
  10. Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part VIII
  11. Characterizing Publicly Available Tabular Health Datasets for Responsible Machine Learning
  12. Cherry-Picking in Time Series Forecasting: How to Select Datasets to Make Your Model Shine
  13. Does Improving Forecasting Accuracy Also Improve Financial Utility? A Case Study with Binary Options
  14. Evaluating Predictive Maintenance Models in the Presence of Reflexivity: A Case Study in Pharmaceutical Manufacturing
  15. Evaluating Transfer Learning Methods on Real-World Data Streams: A Case Study in Financial Fraud Detection
  16. MASTFM: Meta-learning and Data Augmentation to Stress Test Forecasting Models
  17. Read-write LSTM: A Novel Approach Integrating Backpropagation to Data in LSTM
  18. SPATA: Systematic Pattern Analysis for Detailed and Transparent Data Cards
  19. UxV-DPN: Utility-vs-Value Data Pricing and Negotiation Mechanism in Machine Learning Data Marketplace
  20. Fair-OBNC: Correcting Label Noise for Fairer Datasets
  21. RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms