Zhixiang Eddie Xu

Artificial Intelligence · 2012–2014

A researcher in the Science corpus: 4 papers; trusts 43 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it; #6,280 of 35,345 by trust here, #6,956 by citations
• Computer Vision and Pattern Recognition — 20 citations into it
• Optimization & Training — 16 citations into it
• Representation & Self-Supervised Learning — 13 citations into it; #947 of 3,145 by trust here, #1,012 by citations
• Statistical Learning Theory — 12 citations into it
• Statistics and Probability — 10 citations into it

Whom Zhixiang Eddie Xu trusts overall

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

1. Jerome H. Friedman
2. Bernhard Schölkopf
3. Christopher K. I. Williams
4. Leo Breiman
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Olivier Chapelle
8. Radford M. Neal
9. Paul A. Viola
10. Volker Roth

Who trusts Zhixiang Eddie Xu overall

1. Garrett Wilson
2. Gao Huang
3. Kilian Q. Weinberger
4. Matt J. Kusner
5. Rodrigo Nogueira
6. Jacob V. Gardner
7. Yoshua Bengio
8. Niek Tax
9. Christos Louizos
10. Xilun Chen

Papers from Zhixiang Eddie Xu's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Marginalized Denoising Autoencoders for Domain Adaptation (2012) — 838 citations
• The Greedy Miser: Learning under Test-time Budgets (2012) — 123 citations
• Gradient boosted feature selection (2014) — 204 citations
• Bayesian Optimization with Inequality Constraints (2014) — 597 citations