Rong Gong

Signal Processing · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 10 citations into it; #4,902 of 7,572 by trust here, #6,836 by citations
• Artificial Intelligence — 8 citations into it
• Model Architectures — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Rong Gong trusts overall

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

1. Sergey Ioffe
2. Tianqi Chen
3. Xavier Glorot
4. Jerome H. Friedman
5. Christian Szegedy
6. Justin Salamon
7. Yoshua Bengio
8. Dmitry Bogdanov
9. Carlos Guestrin
10. Antoine Bordes

Who trusts Rong Gong overall

1. Eduardo Fonseca

Papers from Rong Gong's perspective

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

Their papers

• A Simple Fusion of Deep and Shallow Learning for Acoustic Scene Classification (2018) — 12 citations
• Acoustic Scene Classification by Ensembling Gradient Boosting Machine and Convolutional Neural Networks (2017) — 29 citations