Chao Zhou

Finance · with Gao · 2015–2017

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Finance — 22 citations into it
• Optimization & Training — 16 citations into it; #1,846 of 2,601 by trust here, #2,428 by citations
• Management Science and Operations Research — 14 citations into it
• Artificial Intelligence — 9 citations into it
• Computational Mechanics — 7 citations into it

Whom Chao Zhou trusts overall

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

1. Richard H. Byrd
2. Aaron Defazio
3. Anatoli B. Juditsky
4. Jorge Nocedal
5. Francis R. Bach
6. M. Kobylanski
7. Yurii E. Nesterov
8. Donald Goldfarb
9. Arkadi Nemirovski
10. Guanghui Lan

Who trusts Chao Zhou overall

1. Dmitrii Ostrovskii
2. Wenbo Gao
3. S. Meng
4. Raghu Bollapragada
5. Umut Simsekli
6. Francis R. Bach
7. Donald Goldfarb
8. Sharan Vaswani
9. Dheevatsa Mudigere
10. Çağatay Yıldız

Papers from Chao Zhou's perspective

Ordered by how strongly the researchers Chao Zhou 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. Stochastic Approximation approach to Stochastic Programming
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
8. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. A Stochastic Approximation Method

Their papers

• Stochastic control for a class of nonlinear kernels and applications (2015) — 67 citations
• Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values (2017) — 26 citations