Lin Zhang

Computer Vision and Pattern Recognition · with Bao · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Lin Zhang trusts overall

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

1. Alex Krizhevsky

Papers from Lin Zhang's perspective

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

1. Learning Multiple Layers of Features from Tiny Images
2. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
3. A Model of Inductive Bias Learning
4. Taskonomy: Disentangling Task Transfer Learning
5. Exploiting Task Relatedness for Mulitple Task Learning
6. NUS-WIDE: a real-world web image database from National University of Singapore
7. Deep Visual Domain Adaptation: A Survey
8. ImageNet classification with deep convolutional neural networks
9. Transfer bounds for linear feature learning
10. Estimating Optimal Transformations for Multiple Regression and Correlation.

Their papers

• An Information-Theoretic Approach to Transferability in Task Transfer Learning (2019) — 162 citations
• An Information-Theoretic Metric of Transferability for Task Transfer Learning (2018)