Lingxiao Ma

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 4 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it
• Computer Vision and Pattern Recognition — 53 citations into it
• Graph Learning — 17 citations into it
• Model Architectures — 15 citations into it
• Optimization & Training — 6 citations into it

Whom Lingxiao Ma trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Thomas Kipf
4. Yoshua Bengio
5. Max Welling
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Kaiming He
9. Sergey Ioffe
10. Christian Szegedy

Papers from Lingxiao Ma's perspective

Ordered by how strongly the researchers Lingxiao Ma 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• SeerNet: Predicting Convolutional Neural Network Feature-Map Sparsity Through Low-Bit Quantization (2019) — 80 citations
• Dense-to-Sparse Gate for Mixture-of-Experts (2021) — 36 citations
• Rammer: Enabling Holistic Deep Learning Compiler Optimizations with rTasks (2020) — 200 citations
• NeuGraph: Parallel Deep Neural Network Computation on Large Graphs (2019) — 299 citations