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Lynn Pepin

2 accepted papers

2021

Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation

IJCAI 2021poster

Network pruning is a widely used technique to reduce computation cost and model size for deep neural networks. However, the typical three-stage pipeline, i.e., training, pruning and retraining (fine-tuning) significantly increases the overall training trails. In this paper, we develop a systematic w…

2020

Data-Driven Distributionally Robust Electric Vehicle Balancing for Mobility-on-Demand Systems under Demand and Supply Uncertainties

IROS 2020poster

As electric vehicle (EV) technologies become mature, EV has been rapidly adopted in modern transportation systems, and is expected to provide future autonomous mobility-on-demand (AMoD) service with economic and societal benefits. However, EVs require frequent recharges due to their limited and unpr…

Cited by 27SourceScholar