Daniel Kane

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it; #34,056 of 35,345 by trust here, #26,682 by citations
• Optimization & Training — 15 citations into it; #2,536 of 2,601 by trust here, #2,162 by citations
• Computational Mechanics — 7 citations into it; #9,569 of 10,001 by trust here, #6,877 by citations
• Computer Vision and Pattern Recognition — 6 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Daniel Kane trusts overall

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

1. Alex Krizhevsky
2. Chih-Jen Lin
3. Nikko Ström
4. Dan Alistarh
5. Sebastian U. Stich
6. Reza Shokri
7. Shai Shalev-Shwartz
8. Ananda Theertha Suresh
9. Ú. Erlingsson
10. Stelios D. Georgiou

Who trusts Daniel Kane overall

1. Wei-Ning Chen
2. Yuqing Du
3. Peter Kairouz
4. Antonious M. Girgis

Papers from Daniel Kane's perspective

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

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

Their papers

• vqSGD: Vector Quantized Stochastic Gradient Descent (2022) — 136 citations