Group knowledge transfer: Federated learning of large cnns at the edge
C He, M Annavaram… - Advances in Neural …, 2020 - proceedings.neurips.cc
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
C He, M Annavaram, S Avestimehr - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
C He, M Annavaram… - Advances in Neural …, 2020 - proceedings.neurips.cc
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …
[PDF][PDF] Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
CHMAS Avestimehr - proceedings.nips.cc
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …
[PDF][PDF] Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
CHMAS Avestimehr - arXiv preprint arXiv:2007.14513, 2020 - openreview.net
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …
Group knowledge transfer: federated learning of large CNNs at the edge
C He, M Annavaram, S Avestimehr - Proceedings of the 34th …, 2020 - dl.acm.org
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
C He, M Annavaram, S Avestimehr - arXiv preprint arXiv:2007.14513, 2020 - arxiv.org
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …
[PDF][PDF] Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
C He, M Annavaram - … in Neural Information Processing Systems 33 …, 2020 - par.nsf.gov
Scaling up the convolutional neural network (CNN) size (eg, width, depth, etc.) is known to
effectively improve model accuracy. However, the large model size impedes training on …
effectively improve model accuracy. However, the large model size impedes training on …