Lizi Liao
Artificial Intelligence · 2017
A researcher in the Science corpus: 2 papers; trusts 52 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 46 citations into it; #6,290 of 35,345 by trust here, #3,878 by citations
- Information Systems — 35 citations into it; #801 of 8,771 by trust here, #246 by citations
- Computer Vision and Pattern Recognition — 31 citations into it; #5,088 of 21,575 by trust here, #3,089 by citations
- Representation & Self-Supervised Learning — 24 citations into it; #858 of 3,145 by trust here, #554 by citations
- Recommender Systems — 14 citations into it; #50 of 233 by trust here, #20 by citations
- Statistical and Nonlinear Physics — 14 citations into it
- Management Science and Operations Research — 13 citations into it
- Graph Learning — 9 citations into it
Whom Lizi Liao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Xiangnan He
- Yoshua Bengio
- Alex Krizhevsky
- Kaiming He
- Ruslan Salakhutdinov
- Yehuda Koren
- Jimmy Ba
- Sergey Ioffe
Who trusts Lizi Liao overall
- Xiangnan He
- Xiang Wang
- Yongfeng Zhang
- Chen Gao
- Fuli Feng
- Xu Chen
- Yi Tay
- Tat-seng Chua
- Benedek Rozemberczki
- Wang-Cheng Kang
Papers from Lizi Liao's perspective
Ordered by how strongly the researchers Lizi Liao 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Neural Collaborative Filtering (2017) — 7,164 citations
- Attributed Social Network Embedding (2017) — 417 citations