Christoph Spiegel

Optimization & Training · 2020

A researcher in the Science corpus: 1 paper; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 18 citations into it
• Artificial Intelligence — 15 citations into it
• Computational Mechanics — 9 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Christoph Spiegel trusts overall

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

1. Alex Krizhevsky
2. Tong Zhang
3. Matthew D. Zeiler
4. Diederik P. Kingma
5. Chih-Jen Lin
6. Martin Jaggi
7. Geoffrey E. Hinton
8. John C. Duchi
9. Rie Johnson
10. L. Eon Bottou

Papers from Christoph Spiegel's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Projection-Free Adaptive Gradients for Large-Scale Optimization (2020) — 13 citations