El Mahdi El Mhamdi
Artificial Intelligence · 9 papers · 2016–2019
A researcher in the Science corpus: 9 papers; trusts 106 researchers and is trusted by 84 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 99 citations into it; #5,079 of 35,345 by trust here, #9,275 by citations
- Optimization & Training — 64 citations into it
- Computer Vision and Pattern Recognition — 36 citations into it
- Safety, Robustness & Interpretability — 22 citations into it; #143 of 2,251 by trust here, #378 by citations
- ML Systems & Hardware — 21 citations into it
- Electrical and Electronic Engineering — 20 citations into it; #4,715 of 16,539 by trust here, #13,553 by citations
- Reinforcement Learning — 17 citations into it
- Algorithms & Complexity — 16 citations into it
Whom El Mahdi El Mhamdi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yann LeCun
- L. Eon Bottou
- Geoffrey E. Hinton
- Simon S. Haykin
- Alex Krizhevsky
- Yoshua Bengio
- Rachid Guerraoui
- Seif Haridi
- Ilya Sutskever
- Paul J. Werbos
Who trusts El Mahdi El Mhamdi overall
- Rachid Guerraoui
- Cong Xie
- Virat Shejwalkar
- Lie He
- El-Mahdi El-Mhamdi
- Sébastien Rouault
- Sai Praneeth Karimireddy
- Deepesh Data
- Hanlin Tang
- Minghong Fang
Papers from El Mahdi El Mhamdi's perspective
Ordered by how strongly the researchers El Mahdi El Mhamdi 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- The Hidden Vulnerability of Distributed Learning in Byzantium (2018) — 1,041 citations
- On the Robustness of a Neural Network (2017) — 20 citations
- When Neurons Fail (2017) — 37 citations
- SGD: Decentralized Byzantine Resilience (2019) — 19 citations
- Asynchronous Byzantine Machine Learning (2018) — 41 citations
- Byzantine-Tolerant Machine Learning (2017) — 88 citations
- Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent (2017) — 2,816 citations
- Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning (2017) — 29 citations
- When Neurons Fail - Technical Report (2016) — 7 citations