Ching-Hsiang Chu

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 3 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 76 citations into it
• Computer Vision and Pattern Recognition — 56 citations into it
• Model Architectures — 15 citations into it

Whom Ching-Hsiang Chu trusts overall

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

1. Alex Krizhevsky
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Andrew Zisserman
6. Yann LeCun

Papers from Ching-Hsiang Chu's perspective

Ordered by how strongly the researchers Ching-Hsiang Chu 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. Attention is All you Need (Neural Information Processing Systems)
4. Going deeper with convolutions
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
9. Long Short-Term Memory
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL? (2017) — 51 citations
• Software-hardware co-design for fast and scalable training of deep learning recommendation models (2021) — 209 citations
• High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models (2021) — 49 citations