Shuang Qiu
Artificial Intelligence · with Liu · 2018–2021
A researcher in the Science corpus: 5 papers; trusts 34 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 101 citations into it; #25,198 of 35,345 by trust here, #23,731 by citations
- Optimization & Training — 47 citations into it
- Computer Networks and Communications — 44 citations into it
- Management Science and Operations Research — 38 citations into it; #8,266 of 11,946 by trust here, #6,024 by citations
- Natural Language Processing — 28 citations into it
- Evaluation & Benchmarks — 7 citations into it
Whom Shuang Qiu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Shai Shalev-Shwartz
- Lijun Zhang
- Elad Hazan
- Diederik P. Kingma
- Yoshua Bengio
- Geoffrey E. Hinton
- András György
- Alex Krizhevsky
- John C. Duchi
- Martin A. Zinkevich
Who trusts Shuang Qiu overall
Papers from Shuang Qiu's perspective
Ordered by how strongly the researchers Shuang Qiu trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Learning Multiple Layers of Features from Tiny Images
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Central Server Free Federated Learning over Single-sided Trust Social Networks (2019) — 80 citations
- Proximal Online Gradient Is Optimum for Dynamic Regret: A General Lower Bound (2021) — 13 citations
- $\texttt{DeepSqueeze}$: Decentralization Meets Error-Compensated Compression (2019) — 54 citations
- Proximal Online Gradient is Optimum for Dynamic Regret (2018) — 7 citations
- Low-Resource Generation of Multi-hop Reasoning Questions (2020) — 15 citations