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Grow, prune or select data: which technique allows the most energy-efficient neural network training?

, , , , and . ICTAI, page 303-308. IEEE, (2023)

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Heterogeneous IoT/LTE ProSe virtual infrastructure for disaster situations., , , and . J. Netw. Comput. Appl., (April 2023)New key management schemes for resource constrained wireless sensor networks.. WOWMOM, page 1-3. IEEE Computer Society, (2011)On data selection for the energy efficiency of neural networks: Towards a new solution based on a dynamic selectivity ratio., , and . ICTAI, page 325-332. IEEE, (2023)Grow, prune or select data: which technique allows the most energy-efficient neural network training?, , , , and . ICTAI, page 303-308. IEEE, (2023)Service Oriented D2D Efficient Communication for Post-Disaster Management., , , and . IWCMC, page 970-975. IEEE, (2020)Cooperative Deep Reinforcement Learning for Dynamic Pollution Plume Monitoring Using a Drone Fleet., , , , and . IEEE Internet Things J., 11 (5): 7325-7338 (2024)Evaluating Regression Models for Temporal Prediction of Wi-Fi Device Mobility., , and . Wirel. Pers. Commun., 116 (3): 2169-2186 (2021)Leveraging Predictability for Global Optimization of IoT Networks., , , and . ICC, page 3586-3591. IEEE, (2022)On the Regression and Assimilation for Air Quality Mapping Using Dense Low-Cost WSN., , , , and . AINA, volume 1151 of Advances in Intelligent Systems and Computing, page 566-578. Springer, (2020)Route Selection in Low-Cost Participatory Mobile Sensing of Air Quality., , and . CCNC, page 302-310. IEEE, (2024)