Gradient flow in sparse neural networks and how lottery tickets win
Abstract Sparse Neural Networks (NNs) can match the generalization of dense NNs using a
fraction of the compute/storage for inference, and have the potential to enable efficient …
fraction of the compute/storage for inference, and have the potential to enable efficient …
Prune and tune ensembles: low-cost ensemble learning with sparse independent subnetworks
T Whitaker, D Whitley - Proceedings of the AAAI Conference on Artificial …, 2022 - ojs.aaai.org
Ensemble Learning is an effective method for improving generalization in machine learning.
However, as state-of-the-art neural networks grow larger, the computational cost associated …
However, as state-of-the-art neural networks grow larger, the computational cost associated …
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 …
networks, this study investigates the actual energy consumption, as measured by node-level …