Sergey G. Rusakov

Optimization & Training · 2019

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 35 citations into it
• Artificial Intelligence — 23 citations into it
• Computational Mechanics — 18 citations into it

Whom Sergey G. Rusakov trusts overall

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

1. Jorge Nocedal
2. L. Eon Bottou
3. Matthew D. Zeiler
4. Diederik P. Kingma
5. Yann LeCun
6. Geoffrey E. Hinton
7. David P. Woodruff
8. Edo Liberty
9. Jimmy Ba
10. John C. Duchi

Papers from Sergey G. Rusakov's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
7. Learning Multiple Layers of Features from Tiny Images
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Scaling Up Quasi-newton Algorithms: Communication Efficient Distributed SR1 (2019) — 17 citations