IEEE SWISS CSS SEMINAR - BIG Hype: Best Intervention in Games via Distributed Hypergradient Descent
We are delighted to invite you to a seminar by Mr. Pangiotis Grontas, the recipient of the IEEE CSS Swiss Chapter Young Author Best Journal Paper Award 2025, who will present his award-winning research.
The seminar can be followed in room ME C2 405 of the EPFL ME building and on Zoom. #control #data-driven #learning #systems #optimization
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- EPFL
- Station 9
- Lausanne, Switzerland
- Switzerland 1015
- Building: MEC building
- Room Number: ME C2 405
Speakers
Panagiotis Grontas of ETH Zürich
BIG Hype: Best Intervention in Games via Distributed Hypergradient Descent
Hierarchical decision making problems, such as bilevel programs and Stackelberg games, are attracting increasing interest in both the engineering and machine learning communities. Yet, existing solution methods lack either convergence guarantees or computational efficiency, due to the absence of smoothness and convexity. In this work, we bridge this gap by designing BIG Hype, a first-order hypergradient-based algorithm for Stackelberg games, and mathematically establishing its convergence using tools from nonsmooth analysis. To evaluate the hypergradient, namely, the gradient of the upper-level objective, we develop an online scheme that simultaneously computes the lower-level equilibrium and its Jacobian. We demonstrate BIG Hype’s potential by deploying it on various large-scale bilevel problems, such as demand response, traffic routing, and recommender systems.
Biography:
Panagiotis Grontas is a doctoral student in the Automatic Control Laboratory (IfA) at ETH Zürich, supervised by John Lygeros. He received an M.Sc. degree with distinction in Robotics, Systems, and Controls from ETH Zürich, and a Diploma degree in Mechanical Engineering from the National Technical University of Athens. He is a recipient of the ETH Medal for outstanding Master’s theses and the IEEE CSS Swiss Chapter Young Author Best Journal Paper Award 2025. His research is focused on the broad intersection of optimization, machine learning, and control.
Address:Italy