Uri Heinemann

Statistical Learning Theory · 2016

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Uri Heinemann trusts overall

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

1. Christopher K. I. Williams
2. Youngmin Cho
3. Robert Gens
4. Alex Krizhevsky
5. Julien Mairal
6. Geoffrey E. Hinton
7. Lawrence K. Saul
8. Shai Shalev-Shwartz
9. Pedro M. Domingos
10. Ilya Sutskever

Who trusts Uri Heinemann overall

1. Tao Lei
2. Wengong Jin

Papers from Uri Heinemann's perspective

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

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

Their papers

• Improper Deep Kernels (2016) — 10 citations