Yichao Wu

Artificial Intelligence · 2007–2020

A researcher in the Science corpus: 12 papers; trusts 359 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 115 citations into it; #10,996 of 35,345 by trust here, #9,465 by citations
• Computer Vision and Pattern Recognition — 113 citations into it
• Statistics and Probability — 80 citations into it; #1,788 of 12,932 by trust here, #2,693 by citations
• Efficiency & Compression — 50 citations into it
• Optimization & Training — 40 citations into it
• Model Architectures — 35 citations into it
• Statistical Learning Theory — 15 citations into it
• Management Science and Operations Research — 15 citations into it

Whom Yichao Wu trusts overall

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

1. Robert Tibshirani
2. Jianqing Fan
3. Hui Zou
4. Jerome H. Friedman
5. Ji Zhu
6. Trevor J. Hastie
7. Runze Li
8. Leo Breiman
9. Grace Wahba
10. Alex Krizhevsky

Who trusts Yichao Wu overall

1. Yufeng Liu
2. Daniel J. Hsu
3. Tan Minh Nguyen
4. Heng Lian
5. Jianqing Fan
6. Eun Ryung Lee
7. Lina Liao
8. Sangdon Park
9. Ü. Dogan
10. Xiaoping Zhou

Papers from Yichao Wu's perspective

Ordered by how strongly the researchers Yichao Wu 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
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. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Correlation Congruence for Knowledge Distillation (2019) — 645 citations
• Knowledge Distillation via Route Constrained Optimization (2019) — 203 citations
• Online Knowledge Distillation via Collaborative Learning (2020) — 374 citations
• Dynamic Recursive Neural Network (2019) — 62 citations
• NETWORK EXPLORATION VIA THE ADAPTIVE LASSO AND SCAD PENALTIES (2009) — 434 citations
• Continuously additive models for nonlinear functional regression (2013) — 70 citations
• Robust Truncated Hinge Loss Support Vector Machines (2007) — 407 citations
• Variable Selection via A Combination of the L0 and L1 Penalties (2007) — 98 citations
• Varying-coefficient functional linear regression (2010) — 63 citations
• Ultrahigh dimensional feature selection: beyond the linear model (2009) — 489 citations
• Stepwise multiple quantile regression estimation using non-crossing constraints (2009) — 110 citations
• VARIABLE SELECTION IN QUANTILE REGRESSION (2009) — 457 citations