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Measuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations
Addressing the so-called ``Red-AI'' trend of rising energy consumption by large-scale neural networks, this study investigates the actual energy consumption, as measured by node-level watt-meters, of training various fully connected neural network architectures.
A Machine Learning Method for Predicting Traffic Signal Timing from Probe Vehicle Data
In this paper, we present a machine learning (ML) method for estimating traffic signal timing information from vehicle probe data.
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