Mike Tse

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 59 citations into it
• Federated & Distributed Learning — 35 citations into it
• Computer Networks and Communications — 7 citations into it
• Electrical and Electronic Engineering — 7 citations into it

Whom Mike Tse trusts overall

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

1. Dianbo Liu
2. Li Huang
3. Takayuki Nishio
4. Umair Mohammad

Papers from Mike Tse's perspective

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

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

Their papers

• A review of applications in federated learning (2020) — 1,458 citations