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math.OC2023
SCQPTH: an efficient differentiable splitting method for convex quadratic programming
Andrew Butler
We present SCQPTH: a differentiable first-order splitting method for convex quadratic programs. The SCQPTH framework is based on the alternating direction method of multipliers (AD…
math.OC2021★ 2 cited
Efficient differentiable quadratic programming layers: an ADMM approach
Andrew Butler, Roy Kwon
Recent advances in neural-network architecture allow for seamless integration of convex optimization problems as differentiable layers in an end-to-end trainable neural network. In…
math.OC2021
Data-driven integration of norm-penalized mean-variance portfolios
Andrew Butler, Roy H. Kwon
Mean-variance optimization (MVO) is known to be sensitive to estimation error in its inputs. Norm penalization of MVO programs is a regularization technique that can mitigate the a…