Francisco Herrera
Artificial Intelligence · with L'opez · 2022
A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 80 citations into it
- Federated & Distributed Learning — 26 citations into it
- Privacy & Security — 25 citations into it
- Computer Vision and Pattern Recognition — 16 citations into it
- Efficiency & Compression — 6 citations into it
- Optimization & Training — 6 citations into it
- Computational Theory and Mathematics — 5 citations into it
Whom Francisco Herrera trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Oded Goldreich
- Yann LeCun
- Geoffrey E. Hinton
- Alex Krizhevsky
- H. Brendan McMahan
- Amos Beimel
- Yoshua Bengio
- Yehuda Lindell
- David P. Woodruff
- Cynthia Dwork
Papers from Francisco Herrera's perspective
Ordered by how strongly the researchers Francisco Herrera trusts endorse each paper. Same corpus, a different order for every researcher.
- Gradient-based learning applied to document recognition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)