Enhancing Fairness and Performance in Machine Learning Models: A Multi-Task Learning Approach with Monte-Carlo Dropout and Pareto Optimality

Documenti analoghi

• Fairness-Driven LLM-based Causal Discovery with Active Learning and Dynamic Scoring
  di: Zanna, Khadija, et al.
  Pubblicazione: (2025)
• Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approach
  di: Zanna, Khadija, et al.
  Pubblicazione: (2025)
• Rethinking Fair Representation Learning for Performance-Sensitive Tasks
  di: Jones, Charles, et al.
  Pubblicazione: (2024)
• Fairness in Multi-Task Learning via Wasserstein Barycenters
  di: Hu, François, et al.
  Pubblicazione: (2023)
• FairMT: Fairness for Heterogeneous Multi-Task Learning
  di: Hu, Guanyu, et al.
  Pubblicazione: (2025)