2 citations · 3 across the 6 of their papers we have counts for
6 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…
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…
Model-Free Learning and Optimal Policy Design in Multi-Agent MDPs Under Probabilistic Agent Dropout
Carmel Fiscko, Soummya Kar, Bruno Sinopoli
This work studies a multi-agent Markov decision process (MDP) that can undergo agent dropout and the computation of policies for the post-dropout system based on control and sampli…
Corrected: On Confident Policy Evaluation for Factored Markov Decision Processes with Node Dropouts
Carmel Fiscko, Soummya Kar, Bruno Sinopoli
In this work we investigate an importance sampling approach for evaluating policies for a structurally time-varying factored Markov decision process (MDP), i.e. the policy's value…
ECCO: Equivalent Circuit Controlled Optimization
Aayushya Agarwal, Carmel Fiscko, Soummya Kar +2
We propose an adaptive optimization algorithm for solving unconstrained scaled gradient flow problems that achieves fast convergence by controlling the optimization trajectory shap…
Cluster-Based Control of Transition-Independent MDPs
Carmel Fiscko, Soummya Kar, Bruno Sinopoli
This work studies efficient solution methods for cluster-based control policies of transition-independent Markov decision processes (TI-MDPs). We focus on control of multi-agent sy…