Tianyi Chen
Artificial Intelligence · with Giannakis · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 47 citations into it; #14,775 of 35,345 by trust here, #15,004 by citations
- Optimization & Training — 38 citations into it; #1,406 of 2,601 by trust here, #1,468 by citations
- Computational Mechanics — 20 citations into it; #3,819 of 10,001 by trust here, #3,275 by citations
- Computer Networks and Communications — 10 citations into it
- Statistics and Probability — 8 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Tianyi Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. Eon Bottou
- Yann LeCun
- Yurii E. Nesterov
- Tong Zhang
- Rie Johnson
- Yuchen Zhang
- Virginia Smith
- Yoshua Bengio
- Geoffrey E. Hinton
- Ohad Shamir
Who trusts Tianyi Chen overall
- Jihong Park
- Mingzhe Chen
- Anis Elgabli
- Mohammad Mohammadi Amiri
- Deniz Gündüz
- Tomer Sery
- Hanlin Tang
- Tao Sun
- Yuanming Shi
- Chaouki Ben Issaid
Papers from Tianyi Chen's perspective
Ordered by how strongly the researchers Tianyi Chen 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
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- 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
- Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks (2019) — 237 citations
- LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning (2018) — 329 citations