Yiqiang Chen

Artificial Intelligence · 2006–2021

A researcher in the Science corpus: 10 papers; trusts 343 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 162 citations into it; #16,123 of 35,345 by trust here, #7,172 by citations
• Computer Vision and Pattern Recognition — 106 citations into it; #12,135 of 21,575 by trust here, #5,205 by citations
• Representation & Self-Supervised Learning — 64 citations into it
• Signal Processing — 32 citations into it
• Electrical and Electronic Engineering — 24 citations into it; #10,696 of 16,539 by trust here, #9,631 by citations
• Computer Networks and Communications — 23 citations into it; #7,254 of 9,886 by trust here, #2,478 by citations
• Biomedical Engineering — 19 citations into it
• Cancer Research — 17 citations into it; #1,435 of 1,780 by trust here, #1,399 by citations

Whom Yiqiang Chen trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Sinno Jialin Pan
4. Alex Krizhevsky
5. Kaiming He
6. Yann LeCun
7. Diederik P. Kingma
8. Ilya Sutskever
9. Bernhard Schölkopf
10. Jindong Wang

Who trusts Yiqiang Chen overall

1. Jindong Wang
2. Qiong Wu
3. Dinh C. Nguyen
4. Azadeh Kushki
5. Chaohui Yu
6. Xuefei Yin
7. Li Li
8. M. Mohammadi
9. Angela Zhang
10. Sreenivasan Ramasamy Ramamurthy

Papers from Yiqiang Chen's perspective

Ordered by how strongly the researchers Yiqiang Chen 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Visual Domain Adaptation with Manifold Embedded Distribution Alignment (2018) — 651 citations
• Balanced Distribution Adaptation for Transfer Learning (2017) — 540 citations
• Transfer Learning with Dynamic Adversarial Adaptation Network (2019) — 388 citations
• FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare (2019) — 933 citations
• Weighted extreme learning machine for imbalance learning (2013) — 733 citations
• Stratified Transfer Learning for Cross-domain Activity Recognition (2017) — 244 citations
• Power-efficient access-point selection for indoor location estimation (2006) — 298 citations
• Semi-supervised deep extreme learning machine for Wi-Fi based localization (2015) — 88 citations
• Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals (2021) — 342 citations
• Deep Learning for Sensor-based Activity Recognition: A Survey (2017) — 1,854 citations