A large-scale study on the impact of behavioral metric learning in deep RL, conceptually unifying and evaluating recent methods spanning 370 tasks with diverse noise settings.
A large-scale study on the impact of behavioral metric learning in deep RL, conceptually unifying and evaluating recent methods spanning 370 tasks with diverse noise settings.
A novel framework for efficient Constrained Horn Clause (CHC) solving, "Chronosymbolic Learning", which provides fundamentals to unify symbolic-reasoning-based and data-driven approaches synergistically.
Introduce RL to human mobility prediction to address the key challenges in this task.
During my Microsoft internship, we explored an RL-based prototype for match plan generation, which outperformed hand-crafted match plans tuned by experts for years, and was later integrated into Bing.