Explores turning bumper cars into unbumping ones through collision avoidance algorithms and the challenges faced when implementing ellipsoid barrier functions.
Explores inverse design optimization in geometric computing, covering topics such as deployable structures, material-aware design, and programmed materials.
Covers optimization techniques in machine learning, focusing on convexity, algorithms, and their applications in ensuring efficient convergence to global minima.
Discusses optimization techniques in machine learning, focusing on stochastic gradient descent and its applications in constrained and non-convex problems.
