Dmitry Babichev

Optimization & Training · 2018

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 10 citations into it
• Artificial Intelligence — 9 citations into it
• Statistical Learning Theory — 6 citations into it
• Computational Mechanics — 5 citations into it
• Statistics and Probability — 5 citations into it

Whom Dmitry Babichev trusts overall

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

1. Christopher K. I. Williams
2. Francis R. Bach
3. David P. Woodruff
4. Aymeric Dieuleveut
5. John Shawe-Taylor
6. Boris Polyak
7. Daphne Koller
8. John D. Lafferty
9. Eric R. Ziegel
10. Nello Cristianini

Papers from Dmitry Babichev's perspective

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

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

Their papers

• Constant Step Size Stochastic Gradient Descent for Probabilistic Modeling (2018) — 11 citations