Wenyuan Dai

Artificial Intelligence · 2007–2019

A researcher in the Science corpus: 11 papers; trusts 47 researchers and is trusted by 61 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 76 citations into it; #3,628 of 35,345 by trust here, #3,757 by citations
• Natural Language Processing — 22 citations into it
• Representation & Self-Supervised Learning — 22 citations into it; #967 of 3,145 by trust here, #982 by citations
• Computer Vision and Pattern Recognition — 20 citations into it; #19,972 of 21,575 by trust here, #12,172 by citations
• Statistical Learning Theory — 19 citations into it
• Probabilistic & Bayesian Methods — 16 citations into it
• Statistics and Probability — 15 citations into it
• Computational Theory and Mathematics — 12 citations into it

Whom Wenyuan Dai trusts overall

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

1. Thorsten Joachims
2. David G. Lowe
3. Pengcheng Wu
4. Bernhard E. Boser
5. R. Caruana
6. Yiming Yang
7. Kamal Nigam
8. Sugato Basu
9. Arthur P. Dempster
10. Thomas G. Dietterich

Who trusts Wenyuan Dai overall

1. Qiang Yang
2. Xiaojun Wan
3. Sinno Jialin Pan
4. Fuzhen Zhuang
5. Mingsheng Long
6. Gabriella Csurka
7. Jialin Pan
8. Zhiyuan Chen
9. Ying Wei
10. Yu Zhang

Papers from Wenyuan Dai's perspective

Ordered by how strongly the researchers Wenyuan Dai 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Boosting for transfer learning (2007) — 1,878 citations
• Heterogeneous Transfer Learning for Image Clustering via the SocialWeb (2009) — 180 citations
• Topic-bridged PLSA for cross-domain text classification (2008) — 219 citations
• Can chinese web pages be classified with english data source? (2008) — 129 citations
• Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion (2019) — 37 citations
• Mining target users for online marketing based on App Store data (2015) — 10 citations
• Privacy-preserving Transfer Learning for Knowledge Sharing (2018) — 19 citations
• Translated Learning: Transfer Learning across Different Feature Spaces (2008) — 319 citations
• Self-taught clustering (2008) — 244 citations
• Co-clustering based classification for out-of-domain documents (2007) — 387 citations
• Transferring Naive Bayes Classifiers for Text Classification (2007) — 415 citations