Jingrui He
Artificial Intelligence · 2004–2019
A researcher in the Science corpus: 6 papers; trusts 115 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 52 citations into it; #28,474 of 35,345 by trust here, #34,943 by citations
- Computer Vision and Pattern Recognition — 30 citations into it; #12,866 of 21,575 by trust here, #15,162 by citations
- Statistics and Probability — 14 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
- Information Systems — 11 citations into it
- Statistical Learning Theory — 11 citations into it
- Computer Networks and Communications — 9 citations into it
- Optimization & Training — 9 citations into it
Whom Jingrui He trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Dengyong Zhou
- Qiuhua Liu
- Nitesh V. Chawla
- Sanjoy Dasgupta
- Kamal Nigam
- Rie Kubota Ando
- Geoffrey E. Hinton
- Yanmin Sun
- Jason Aaron Edward Weston
- Shibin Parameswaran
Who trusts Jingrui He overall
- Hanghang Tong
- Xianchao Zhang
- Jihang Ye
- Mohammad Rostami
- Liu Yang
- Christos Faloutsos
- Tae Hoon Kim
- Ritendra Datta
- William Stafford Noble
- Yu Zheng
Papers from Jingrui He's perspective
Ordered by how strongly the researchers Jingrui He trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Manifold-ranking based image retrieval (2004) — 389 citations
- Comparing Random Forest with Logistic Regression for Predicting Class-Imbalanced Civil War Onset Data (2016) — 244 citations
- Deep Multimodality Model for Multi-task Multi-view Learning (2019) — 18 citations
- Social Phishing (2018) — 337 citations
- MILEAGE: Multiple Instance LEArning with Global Embedding (2013) — 20 citations
- A Graphbased Framework for Multi-Task Multi-View Learning (2011) — 95 citations