Daniel Rothchild

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 4 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 78 citations into it
• Computer Vision and Pattern Recognition — 39 citations into it
• Electrical and Electronic Engineering — 21 citations into it
• Optimization & Training — 21 citations into it
• Federated & Distributed Learning — 19 citations into it

Whom Daniel Rothchild trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Sebastian U. Stich
3. Ilya Sutskever
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Moses Charikar
7. Sai Praneeth Karimireddy
8. Yann LeCun
9. Diederik P. Kingma
10. Kaiming He

Who trusts Daniel Rothchild overall

1. Dinh C. Nguyen
2. Mingzhe Chen
3. Ming Ding
4. Chaoyang He

Papers from Daniel Rothchild's perspective

Ordered by how strongly the researchers Daniel Rothchild trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Learning Multiple Layers of Features from Tiny Images
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Carbon Emissions and Large Neural Network Training (2021) — 1,164 citations
• The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink (2022) — 465 citations
• FetchSGD: Communication-Efficient Federated Learning with Sketching (2020) — 432 citations
• SqueezeWave: Extremely Lightweight Vocoders for On-device Speech Synthesis (2020) — 27 citations