Yu Zhang

Representation & Self-Supervised Learning · 2013–2015

A researcher in the Science corpus: 3 papers; trusts 78 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Representation & Self-Supervised Learning — 34 citations into it; #1,297 of 3,145 by trust here, #2,957 by citations
• Artificial Intelligence — 24 citations into it; #8,914 of 35,345 by trust here, #25,040 by citations
• Computational Mechanics — 15 citations into it; #2,047 of 10,001 by trust here, #6,287 by citations
• Optimization & Training — 12 citations into it; #1,527 of 2,601 by trust here, #2,378 by citations
• Statistical Learning Theory — 10 citations into it; #380 of 1,038 by trust here, #678 by citations
• Computer Vision and Pattern Recognition — 8 citations into it; #7,545 of 21,575 by trust here, #19,310 by citations
• Civil and Structural Engineering — 5 citations into it
• Computer Networks and Communications — 5 citations into it; #4,152 of 9,886 by trust here, #8,191 by citations

Whom Yu Zhang trusts overall

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

1. Yu Zhang
2. Jianhui Chen
3. Andreas Maurer
4. Dit-Yan Yeung
5. Jonathan Baxter
6. Theodoros Evgeniou
7. Sebastian Thrun
8. R. Caruana
9. Edwin V. Bonilla
10. Rie Kubota Ando

Who trusts Yu Zhang overall

1. Yu Zhang
2. Qiang Yang
3. Sulin Liu
4. Lei Han
5. Dit-Yan Yeung
6. Sinno Jialin Pan
7. Garrett Wilson
8. Yu Zhang
9. Sebastian Ruder
10. Ben Tan

Papers from Yu Zhang's perspective

Ordered by how strongly the researchers Yu Zhang 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Multi-Task Learning and Algorithmic Stability (2015) — 41 citations
• Parallel Multi-task Learning (2015) — 24 citations
• Heterogeneous-Neighborhood-based Multi-Task Local Learning Algorithms (2013) — 28 citations