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math.OC2026
Functional Gradient Descent with Adaptive Representations
Daniel Csillag, Rodrigo Schuller, Pedro Dall'Antonia +3
Functional optimization problems are typically solved by optimizing the parameters of a fixed representation, such as a neural network, resulting in highly nonconvex losses that co…
math.OC2026
Random Gradient-Free Optimization in Infinite Dimensional Spaces
Caio Peixoto, Daniel Csillag, Bernardo F. P. da Costa +1
We propose a new gradient-free method for infinite-dimensional optimization in Hilbert spaces that requires only the computation of directional derivatives. Though functional optim…