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Student Learning Hub: Online Optimization Meets Urban Transportation
November 8 @ 1:00 pm - 2:00 pm
Instructor: Tao Li, New York University
Beginner level: No prior experience required. Basic optimization knowledge would be helpful but not required.
Description: Urban transportation networks are complex and dynamic, and as a result, offline planning alone may not ensure effective real-time management. Therefore, this course introduces online optimization methods with a focus on transportation applications. We’ll start with gradient descent in conventional convex optimization, move to online gradient descent, and briefly explore multi-agent online learning and associated equilibrium convergence. We’ll also discuss challenges in deploying online optimization in urban transportation.