2 citations · 4 across the 5 of their papers we have counts for
5 papers
Towards Hyperparameter-Agnostic DNN Training via Dynamical System Insights
Carmel Fiscko, Aayushya Agarwal, Yihan Ruan +3
We present a stochastic first-order optimization method specialized for deep neural networks (DNNs), ECCO-DNN. This method models the optimization variable trajectory as a dynamica…
Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning
Shimiao Li, Jan Drgona, Shrirang Abhyankar +1
Recent years have seen a rich literature of data-driven approaches designed for power grid applications. However, insufficient consideration of domain knowledge can impose a high r…
An Equivalent Circuit Approach to Distributed Optimization
Aayushya Agarwal, Larry Pileggi
Distributed optimization is an essential paradigm to solve large-scale optimization problems in modern applications where big-data and high-dimensionality creates a computational b…
An Equivalent Circuit Workflow for Unconstrained Optimization
Aayushya Agarwal, Carmel Fiscko, Soummya Kar +2
We introduce a new workflow for unconstrained optimization whereby objective functions are mapped onto a physical domain to more easily design algorithms that are robust to hyperpa…
Equivalent Circuit Programming for Power Flow Analysis and Optimization
Marko Jereminov, Larry Pileggi
The utility of domain-specific knowledge for modeling, simulation, and optimization has been demonstrated for various research problem domains, including power systems. The concept…