Vitaly Kuznetsov

Artificial Intelligence · 2014–2016

A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 73 citations into it
• Optimization & Training — 26 citations into it
• Statistics and Probability — 18 citations into it
• Statistical Learning Theory — 15 citations into it
• Management Science and Operations Research — 10 citations into it
• Control and Systems Engineering — 9 citations into it
• Computational Mechanics — 8 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Vitaly Kuznetsov trusts overall

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

1. Mehryar Mohri
2. Yoav Freund
3. Robert E. Schapire
4. Corinna Cortes
5. Jerome H. Friedman
6. Alexander Rakhlin
7. S. Brandt
8. Peter J. Brockwell
9. Tao Pham Dinh
10. Bin Yu

Who trusts Vitaly Kuznetsov overall

1. Ammar Mohammed
2. Corinna Cortes
3. Elad Hazan
4. Fei Ye
5. Mehryar Mohri
6. Rania Kora
7. Clemens Rosenbaum
8. Holden Lee
9. Adrian G. Bors

Papers from Vitaly Kuznetsov's perspective

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

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

Their papers

• Structured Prediction Theory Based on Factor Graph Complexity (2016) — 62 citations
• AdaNet: Adaptive Structural Learning of Artificial Neural Networks (2016) — 301 citations
• Time series prediction and online learning (2016) — 56 citations
• Learning Theory and Algorithms for Forecasting Non-stationary Time Series (2015) — 89 citations
• Multi-Class Deep Boosting (2014) — 82 citations