Phuong Ha Nguyen

Optimization & Training · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 32 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 54 citations into it; #1,878 of 2,601 by trust here, #1,624 by citations
• Artificial Intelligence — 41 citations into it
• Computational Mechanics — 30 citations into it
• Management Science and Operations Research — 13 citations into it
• Computational Theory and Mathematics — 7 citations into it; #10,279 of 12,182 by trust here, #4,850 by citations
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Phuong Ha Nguyen trusts overall

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

1. Dimitri P. Bertsekas
2. L. Eon Bottou
3. Francis R. Bach
4. Yurii E. Nesterov
5. Chih-Jen Lin
6. Alex Krizhevsky
7. B. Recht
8. Geoffrey E. Hinton
9. Nicolas Le Roux
10. Yann LeCun

Who trusts Phuong Ha Nguyen overall

1. Nicolas Loizou
2. Konstantin Mishchenko
3. Peter Richtárik
4. Ahmed Khaled
5. Eduard A. Gorbunov
6. Robert Mansel Gower
7. Tao Sun

Papers from Phuong Ha Nguyen's perspective

Ordered by how strongly the researchers Phuong Ha Nguyen 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
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. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

Their papers

• SGD and Hogwild! Convergence Without the Bounded Gradients Assumption (2018) — 251 citations
• A Unified Convergence Analysis for Shuffling-Type Gradient Methods (2020) — 100 citations
• New Convergence Aspects of Stochastic Gradient Algorithms (2018) — 78 citations