Research
Fairness in machine learning has predominantly been studied in static classification settings without concern for how decisions change the underlying population over time. Conventional wisdom suggests that fairness criteria promote the long-term well-being of those…
In the first part of the talk, I will introduce Multi-agent Generative Adversarial Imitation Learning, a new framework for multi-agent imitation learning for general Markov games, where we build upon a generalized notion of inverse…
Social and behavioral interventions are a critical tool for governments and communities to tackle deep-rooted societal challenges such as homelessness, disease, and poverty. However, real-world interventions are almost always plagued by limited resources and limited…
