Lior Horesh

Optimization & Training · 2013

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 8 citations into it
• Artificial Intelligence — 7 citations into it

Whom Lior Horesh trusts overall

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

1. Brian Kingsbury
2. James Martens
3. Barak A. Pearlmutter
4. Jorge Nocedal
5. Jonathan Richard Shewchuk
6. Oriol Vinyals
7. Hang Su

Papers from Lior Horesh's perspective

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

1. Large Scale Distributed Deep Networks
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Long Short-Term Memory
7. Deep learning via Hessian-free optimization
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. Fast Exact Multiplication by the Hessian

Their papers

• Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling (2013) — 23 citations