Xianchao Zhang
Artificial Intelligence · 2013–2018
A researcher in the Science corpus: 6 papers; trusts 121 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 74 citations into it; #13,962 of 35,345 by trust here, #24,417 by citations
- Computer Vision and Pattern Recognition — 46 citations into it; #10,086 of 21,575 by trust here, #17,757 by citations
- Representation & Self-Supervised Learning — 30 citations into it
- Computational Mechanics — 12 citations into it
- Signal Processing — 11 citations into it
- Media Technology — 10 citations into it; #2,591 of 3,621 by trust here, #3,318 by citations
- Optimization & Training — 7 citations into it
- Computational Theory and Mathematics — 6 citations into it
Whom Xianchao Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Quanquan Gu
- Jianwen Zhang
- Xiao-Lei Zhang
- Inderjit S. Dhillon
- Shi Zhong
- Theodoros Evgeniou
- Chris H. Q. Ding
- Michael I. Jordan
- Wei Xu
- Andrew Y. Ng
Who trusts Xianchao Zhang overall
Papers from Xianchao Zhang's perspective
Ordered by how strongly the researchers Xianchao Zhang 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)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- 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
- Multi-Task Clustering with Model Relation Learning (2018) — 22 citations
- Multi-Task Multi-View Clustering (2016) — 79 citations
- Self-Adapted Multi-Task Clustering (2016) — 34 citations
- Smart Multitask Bregman Clustering and Multitask Kernel Clustering (2015) — 25 citations
- Multi-Task Multi-View Clustering for Non-Negative Data (2015) — 40 citations
- Smart Multi-Task Bregman Clustering and Multi-Task Kernel Clustering (2013) — 15 citations