Youngmin Cho
Artificial Intelligence · 2009
A researcher in the Science corpus: 1 paper; trusts 72 researchers and is trusted by 84 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 17 citations into it
- Computer Vision and Pattern Recognition — 17 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
- Evaluation & Benchmarks — 5 citations into it
- Statistical Learning Theory — 5 citations into it
- Optimization & Training — 5 citations into it
Whom Youngmin Cho trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Yann LeCun
- Radford M. Neal
- Bernhard Schölkopf
- Francis R. Bach
- Vladimir Naumovich Vapnik
- Aapo Hyvärinen
- Jason Aaron Edward Weston
- Michael I. Jordan
Who trusts Youngmin Cho overall
- Greg Yang
- Julien Mairal
- Jaehoon Lee
- Roman Novak
- Behnam Neyshabur
- Ahmad Salman
- Alberto Bietti
- Francis R. Bach
- Bo Xie
- Li Deng
Papers from Youngmin Cho's perspective
Ordered by how strongly the researchers Youngmin Cho 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Kernel Methods for Deep Learning (2009) — 865 citations