no code implementations • 6 Apr 2023 • Walid Al Misba, Harindra S. Mavikumbure, Md Mahadi Rajib, Daniel L. Marino, Victor Cobilean, Milos Manic, Jayasimha Atulasimha
By comparing our spintronic physical RC approach with state-of-the-art energy load forecasting algorithms, such as LSTMs and RNNs, we conclude that the proposed framework presents good performance in achieving high predictions accuracy, while also requiring low memory and energy both of which are at a premium in hardware resource and power constrained edge applications.
no code implementations • 5 Sep 2022 • Chathurika S. Wickramasinghe, Daniel L. Marino, Harindra S. Mavikumbure, Victor Cobilean, Timothy D. Pennington, Benny J. Varghese, Craig Rieger, Milos Manic
Recent year has brought considerable advancements in Electric Vehicles (EVs) and associated infrastructures/communications.
no code implementations • 25 Feb 2022 • Daniel L. Marino, Chathurika S. Wickramasinghe, Craig Rieger, Milos Manic
Monitoring traffic in computer networks is one of the core approaches for defending critical infrastructure against cyber attacks.
no code implementations • 5 Jun 2019 • Daniel L. Marino, Milos Manic
Centuries of development in natural sciences and mathematical modeling provide valuable domain expert knowledge that has yet to be explored for the development of machine learning models.
no code implementations • 28 Nov 2018 • Daniel L. Marino, Chathurika S. Wickramasinghe, Milos Manic
Adversarial machine learning offers an approach to increase our understanding of these models.
no code implementations • 29 Oct 2016 • Daniel L. Marino, Kasun Amarasinghe, Milos Manic
Experimental results showed that the standard LSTM failed at one-minute resolution data while performing well in one-hour resolution data.
1 code implementation • 25 Aug 2016 • Daniel L. Marino, Milos Manic
While most current trajectory simplification algorithms are tailored for GPS trajectories, our approach focuses on smooth trajectories for robot programming by demonstration recorded using motion capture systems. Two variations of the algorithm are presented: 1. aims to preserve shape and temporal information; 2. preserves only shape information.