Simon Smith

DIDL@Middleware · 2018

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Simon Smith trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yushi Wang
2. Yann LeCun
3. H. Brendan McMahan
4. Jakub Konecný

Who trusts Simon Smith overall

1. Qinbin Li

Papers from Simon Smith's perspective

Ordered by how strongly the researchers Simon Smith trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. The mnist database of handwritten digits
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Learning Multiple Layers of Features from Tiny Images
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Going deeper with convolutions
10. Communication-Efficient Learning of Deep Networks from Decentralized Data

Their papers

• A Performance Evaluation of Federated Learning Algorithms (2018) — 325 citations