An Bian
Artificial Intelligence · 2013–2018
A researcher in the Science corpus: 3 papers; trusts 71 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 57 citations into it; #34,154 of 35,345 by trust here, #19,873 by citations
- Optimization & Training — 44 citations into it
- Computational Mechanics — 39 citations into it
- Computer Networks and Communications — 23 citations into it
- Federated & Distributed Learning — 13 citations into it
- Computational Theory and Mathematics — 10 citations into it
- Numerical Analysis — 10 citations into it
- Mathematical Optimization — 9 citations into it
Whom An Bian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Shai Shalev-Shwartz
- Martin A. Zinkevich
- Yurii E. Nesterov
- Guo-Xun Yuan
- John C. Duchi
- Peter Richtárik
- Ching-pei Lee
- Alex Smola
- Matilde Gargiani
- Geoffrey E. Hinton
Who trusts An Bian overall
- Virginia Smith
- Dhruv Kumar Mahajan
- Simone Forte
- Matilde Gargiani
- Martin Jaggi
- S. Sathiya Keerthi
- Michael I. Jordan
- Hanlin Tang
Papers from An Bian's perspective
Ordered by how strongly the researchers An Bian 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
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- 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 Distributed Second-Order Algorithm You Can Trust (2018) — 33 citations
- COLA: Decentralized Linear Learning (2018) — 140 citations
- Parallel Coordinate Descent Newton Method for Efficient $\ell_1$-Regularized Minimization (2013) — 7 citations