Quoc Tran-Dinh
Artificial Intelligence · 1988–2020
A researcher in the Science corpus: 5 papers; trusts 45 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 50 citations into it; #20,184 of 35,345 by trust here, #22,463 by citations
- Optimization & Training — 48 citations into it; #1,707 of 2,601 by trust here, #2,081 by citations
- Computational Mechanics — 43 citations into it; #5,489 of 10,001 by trust here, #5,350 by citations
- Statistics and Probability — 17 citations into it
- Computational Theory and Mathematics — 13 citations into it
- Mathematical Optimization — 12 citations into it
- Management Science and Operations Research — 11 citations into it
- Numerical Analysis — 10 citations into it; #2,060 of 3,586 by trust here, #2,430 by citations
Whom Quoc Tran-Dinh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Chih-Jen Lin
- Tong Zhang
- Rie Johnson
- L. Eon Bottou
- Lam M. Nguyen
- Alex Krizhevsky
- Zeyuan Allen-Zhu
- Aaron Defazio
- Saeed Ghadimi
Who trusts Quoc Tran-Dinh overall
- Nicolas Loizou
- Gauthier Gidel
- Kfir Yehuda Levy
- Konstantin Mishchenko
- Hugo Berard
- Kwangjun Ahn
- Ahmed Khaled
Papers from Quoc Tran-Dinh's perspective
Ordered by how strongly the researchers Quoc Tran-Dinh trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A Universal Primal-Dual Convex Optimization Framework (2015) — 63 citations
- Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization (2019) — 60 citations
- Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function (2020) — 28 citations
- A Unified Convergence Analysis for Shuffling-Type Gradient Methods (2020) — 100 citations
- of Computer Science (1988)