1 citations · 1 across the 9 of their papers we have counts for
10 papers
Duality and Error for Predictively Oriented Inference
Aurya Javeed, Drew P. Kouri, Teresa Portone +1
Predictively oriented (PrO) inference quantifies uncertainty by selecting a distribution over model parameters to optimize a scoring rule applied to the induced predictive distribu…
Statistical Inference for Scenario-Based Dynamic Optimization under Uncertainty
Aurya Javeed, Johannes Milz
Motivated by batch and semi-batch process operation, we study finite-horizon open-loop dynamic optimization problems with uncertain parameters. A common computational approach repl…
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…
A Parallel-in-Time Multigrid Preconditioner for Optimal Control
Radoslav Vuchkov, Eric C. Cyr, Aurya Javeed +1
We develop a parallel-in-time multigrid preconditioner for augmented systems. These saddle-point systems are foundational to numerical optimization. Our preconditioner, when paired…
A Risk Management Perspective on Statistical Estimation and Generalized Variational Inference
Aurya S. Javeed, Drew P. Kouri, Thomas M. Surowiec
Generalized variational inference (GVI) provides an optimization-theoretic framework for statistical estimation that encapsulates many traditional estimation procedures. The typica…
Machine Learning for CUDA+MPI Design Rules
Carl Pearson, Aurya Javeed, Karen Devine
We present a new strategy for automatically exploring the design space of key CUDA+MPI programs and providing design rules that discriminate slow from fast implementations. In such…
An Uncertainty Principle for Estimates of Floquet Multipliers
Aurya Javeed
We derive a Cramér-Rao lower bound for the variance of Floquet multiplier estimates that have been constructed from stable limit cycles perturbed by noise. To do so, we consider pe…
Timing Observations of Diffusions
Aurya Javeed, Giles Hooker
This paper addresses a problem in experimental design: We consider Itô diffusions specified by some and assume that we are allowed to observe their sample paths o…