2 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
Scalable Deep Unfolding of Conic Optimizers
Alex Oshin, Rahul Vodeb Ghosh, Evangelos A. Theodorou
Deep unfolding (DU) accelerates iterative optimizers by introducing learnable components and training them through unrolled iterations, but extending DU to the large-scale semidefi…
Deep FlexQP: Accelerated Nonlinear Programming via Deep Unfolding
Alex Oshin, Rahul Vodeb Ghosh, Augustinos D. Saravanos +1
We propose FlexQP, an always-feasible convex quadratic programming (QP) solver based on an elastic relaxation of the QP constraints. If the original constraints are feasib…
Deep Distributed Optimization for Large-Scale Quadratic Programming
Augustinos D. Saravanos, Hunter Kuperman, Alex Oshin +3
Quadratic programming (QP) forms a crucial foundation in optimization, encompassing a broad spectrum of domains and serving as the basis for more advanced algorithms. Consequently,…
Differentiable Robust Model Predictive Control
Alex Oshin, Hassan Almubarak, Evangelos A. Theodorou
Deterministic model predictive control (MPC), while powerful, is often insufficient for effectively controlling autonomous systems in the real-world. Factors such as environmental…
Parameterized Differential Dynamic Programming
Alex Oshin, Matthew D. Houghton, Michael J. Acheson +2
Differential Dynamic Programming (DDP) is an efficient trajectory optimization algorithm relying on second-order approximations of a system's dynamics and cost function, and has re…