Bicheng Ying
Optimization & Training · 2016–2018
A researcher in the Science corpus: 3 papers; trusts 54 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Optimization & Training — 45 citations into it
- Artificial Intelligence — 44 citations into it; #20,507 of 35,345 by trust here, #27,551 by citations
- Computer Networks and Communications — 41 citations into it; #5,172 of 9,886 by trust here, #5,733 by citations
- Computational Mechanics — 33 citations into it
- Mathematical Optimization — 13 citations into it
- Computational Theory and Mathematics — 11 citations into it
- Computer Vision and Pattern Recognition — 9 citations into it
- Numerical Analysis — 9 citations into it
Whom Bicheng Ying trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ali H. Sayed
- Yurii E. Nesterov
- Angelia Nedić
- Tong Zhang
- Wei Shi
- Dimitri P. Bertsekas
- Rie Johnson
- Yann LeCun
- Shai Shalev-Shwartz
- L. Eon Bottou
Who trusts Bicheng Ying overall
- Khaled Ben Letaief
- Yaochen Hu
- Ali H. Sayed
- Kun Yuan
- Sulaiman A. Alghunaim
- Alexander Olshevsky
- Zhi Li
- Yuanming Shi
- Lucas Cassano
- Peng Liu
Papers from Bicheng Ying's perspective
Ordered by how strongly the researchers Bicheng Ying trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Supervised Learning Under Distributed Features (2018) — 44 citations
- Exact Diffusion for Distributed Optimization and Learning—Part I: Algorithm Development (2017) — 249 citations
- On the influence of momentum acceleration on online learning (2016) — 67 citations