1 citations · 1 across the 9 of their papers we have counts for
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SUPN: Shallow Universal Polynomial Networks for Efficient Function Approximation
Zachary Morrow, Michael Penwarden, Brian Chen +3
Deep neural networks (DNNs) and Kolmogorov-Arnold networks (KANs) are flexible function approximators, but their accuracy can require substantial network depth, width, and trainabl…
ProxSTORM -- A Stochastic Trust-Region Algorithm for Nonsmooth Optimization
Robert J. Baraldi, Aurya Javeed, Drew P. Kouri +1
We develop a stochastic trust-region algorithm for minimizing the sum of a Lipschitz-smooth but possibly nonconvex function and a convex but possibly nonsmooth function. Such a pro…
A Million-Point Fast Trajectory Optimization Solver
A. Javeed, D. P. Kouri, D. Ridzal +2
One might argue that solving a trajectory optimization problem over a million grid points is preposterous. How about solving such a problem at an incredibly fast computational time…