Shaden Smith
Artificial Intelligence · 2015–2022
A researcher in the Science corpus: 5 papers; trusts 13 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 206 citations into it
- Natural Language Processing — 118 citations into it
- Efficiency & Compression — 41 citations into it
- Optimization & Training — 27 citations into it
- Hardware and Architecture — 17 citations into it; #931 of 1,551 by trust here, #447 by citations
- Computational Mathematics — 7 citations into it; #416 of 612 by trust here, #543 by citations
- Management Science and Operations Research — 5 citations into it
Whom Shaden Smith trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Brett W. Bader
- Yoshua Bengio
- Ilya Sutskever
- Jimmy Ba
- Alex Krizhevsky
- Noam Shazeer
- Alec Radford
- Kaiming He
Who trusts Shaden Smith overall
- Jiajia Li
- Jimeng Sun
- Deyao Zhu
- Jun Chen
- Vijay Anand Korthikanti
- Reza Yazdani Aminabadi
- Perttu Hämäläinen
- Wenhu Chen
- R. Vuduc
- Yihan Cao
Papers from Shaden Smith's perspective
Ordered by how strongly the researchers Shaden Smith trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model (2022) — 859 citations
- ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep learning (2021) — 548 citations
- DeepSpeed- Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale (2022) — 640 citations
- BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations
- Tensor-matrix products with a compressed sparse tensor (2015) — 141 citations