2 papers
cs.DS2025
Signal-Aware Workload Shifting Algorithms with Uncertainty-Quantified Predictors
Ezra Johnson, Adam Lechowicz, Mohammad Hajiesmaili
A wide range of sustainability and grid-integration strategies depend on workload shifting, which aligns the timing of energy consumption with external signals such as grid curtail…
cs.LG2022
WeightMom: Learning Sparse Networks using Iterative Momentum-based pruning
Elvis Johnson, Xiaochen Tang, Sriramacharyulu Samudrala
Deep Neural Networks have been used in a wide variety of applications with significant success. However, their highly complex nature owing to comprising millions of parameters has…