Rixon Crane
Optimization & Training · 2019
A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Optimization & Training — 7 citations into it
- Artificial Intelligence — 5 citations into it
Whom Rixon Crane trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Yoshua Bengio
- Rie Johnson
- Jorge Nocedal
- David Chin-Lung Fong
- Tong Zhang
- Sou-Cheng T. Choi
- Michael A. Saunders
- Jianmin Chen
- Sashank J. Reddi
Papers from Rixon Crane's perspective
Ordered by how strongly the researchers Rixon Crane trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
Their papers
- DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization (2019) — 49 citations