1 citations · 2 across the 10 of their papers we have counts for
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cs.LG2020
Designing Interpretable Approximations to Deep Reinforcement Learning
Nathan Dahlin, Krishna Chaitanya Kalagarla, Nikhil Naik +2
In an ever expanding set of research and application areas, deep neural networks (DNNs) set the bar for algorithm performance. However, depending upon additional constraints such a…
eess.SY2020
A Risk Aware Two-Stage Market Mechanism for Electricity with Renewable Generation
Nathan Dahlin, Rahul Jain
Over the last few decades, electricity markets around the world have adopted multi-settlement structures, allowing for balancing of supply and demand as more accurate forecast info…
eess.SY2020
Scheduling Flexible Non-Preemptive Loads in Smart-Grid Networks
Nathan Dahlin, Rahul Jain
A market consisting of a generator with thermal and renewable generation capability, a set of non-preemptive loads (i.e., loads which cannot be interrupted once started), and an in…