Adaptive Fairness-Aware Online Meta-Learning for Changing Environments

Understand

The fairness-aware online learning framework has arisen as a powerful tool for the continual lifelong learning setting.

• The goal for the learner is to sequentially learn new tasks where they come one after another over time and the learner ensures the statistic parity of the new coming task across different protected sub-populations (e.g.
• race and gender).
• A major drawback of existing methods is that they make heavy use of the i.i.d assumption for data and hence provide static regret analysis for the framework.