Michal Moshkovitz

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Model Architectures — 7 citations into it
• Scaling & Learning Theory — 7 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Michal Moshkovitz trusts overall

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

1. Alex Krizhevsky
2. Shai Shalev-Shwartz
3. Geoffrey E. Hinton
4. Taco Cohen
5. Ohad Shamir
6. Robert Gens
7. Christian Szegedy
8. Ilya Sutskever
9. Max Welling
10. Chiyuan Zhang

Who trusts Michal Moshkovitz overall

1. Ravid Shwartz-Ziv
2. Naftali Tishby

Papers from Michal Moshkovitz's perspective

Ordered by how strongly the researchers Michal Moshkovitz 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
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

• Mixing Complexity and its Applications to Neural Networks (2017) — 11 citations