Daniel Zink

Optimization & Training · 2016

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 11 citations into it; #1,699 of 2,601 by trust here, #2,215 by citations
• Artificial Intelligence — 7 citations into it; #19,976 of 35,345 by trust here, #27,551 by citations

Whom Daniel Zink trusts overall

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

1. Elad Hazan
2. Dan Garber
3. Martin Jaggi
4. Thorsten Joachims

Who trusts Daniel Zink overall

1. Sebastian Pokutta
2. Thomas Kerdreux
3. Alejandro Carderera

Papers from Daniel Zink's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. An algorithm for quadratic programming
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization
5. Block-Coordinate Frank-Wolfe Optimization for Structural SVMs
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. Cutting-plane training of structural SVMs
10. Long Short-Term Memory

Their papers

• Lazifying Conditional Gradient Algorithms (2016) — 59 citations