Dmitriy Drusvyatskiy

Computational Mechanics · 2013–2018

A researcher in the Science corpus: 7 papers; trusts 42 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 43 citations into it; #1,381 of 10,001 by trust here, #2,156 by citations
• Optimization & Training — 38 citations into it; #2,337 of 2,601 by trust here, #2,484 by citations
• Artificial Intelligence — 31 citations into it; #6,169 of 35,345 by trust here, #12,244 by citations
• Computational Theory and Mathematics — 26 citations into it
• Numerical Analysis — 20 citations into it; #467 of 3,586 by trust here, #561 by citations
• Management Science and Operations Research — 16 citations into it
• Mathematical Physics — 13 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it; #18,508 of 21,575 by trust here, #20,271 by citations

Whom Dmitriy Drusvyatskiy trusts overall

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

1. Yurii E. Nesterov
2. Zeyuan Allen-Zhu
3. R. Tyrrell Rockafellar
4. Damek Davis
5. Saeed Ghadimi
6. Asen L. Dontchev
7. Guanghui Lan
8. Boris S. Mordukhovich
9. Bastian Goldlücke
10. Hui Zou

Who trusts Dmitriy Drusvyatskiy overall

1. Damek Davis
2. Hui Zhang
3. Hilal Asi
4. Chi Jin
5. John C. Duchi
6. Michael Arbel
7. Benjamin Grimmer
8. Praneeth Netrapalli
9. Simon Shaolei Du
10. Ion Necoara

Papers from Dmitriy Drusvyatskiy's perspective

Ordered by how strongly the researchers Dmitriy Drusvyatskiy 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. Learning Multiple Layers of Features from Tiny Images
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Et al

Their papers

• Stochastic model-based minimization of weakly convex functions (2018) — 473 citations
• Stochastic subgradient method converges at the rate O(k-1/4) on weakly convex functions (2018) — 113 citations
• Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods (2016) — 394 citations
• Complexity of finding near-stationary points of convex functions stochastically (2018) — 18 citations
• Stochastic Subgradient Method Converges on Tame Functions (2018) — 324 citations
• Subgradient Methods for Sharp Weakly Convex Functions (2018) — 140 citations
• Second-order growth, tilt stability, and metric regularity of the subdifferential (2013) — 97 citations