Covers optimization techniques in machine learning, focusing on convexity, algorithms, and their applications in ensuring efficient convergence to global minima.
Explores the trade-off between complexity and risk in machine learning models, the benefits of overparametrization, and the implicit bias of optimization algorithms.
Explores self-organization in natural systems and foraging strategies of ants, including the Traveling Salesman Problem and Ant Colony Optimization algorithms.
Explores the design and applications of reconfigurable metasurfaces in advanced optics, including switchable magnetic metamaterials and responsive metasurfaces.
