Yossi Arjevani
Artificial Intelligence · 2015–2019
A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 41 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 63 citations into it; #4,757 of 35,345 by trust here, #11,072 by citations
- Optimization & Training — 57 citations into it; #491 of 2,601 by trust here, #1,120 by citations
- Computational Mechanics — 47 citations into it; #867 of 10,001 by trust here, #1,838 by citations
- Computational Theory and Mathematics — 20 citations into it
- Mathematical Optimization — 15 citations into it
- Management Science and Operations Research — 12 citations into it; #8,971 of 11,946 by trust here, #10,392 by citations
- Numerical Analysis — 9 citations into it
- Computer Vision and Pattern Recognition — 7 citations into it
Whom Yossi Arjevani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Ohad Shamir
- Tong Zhang
- Shai Shalev-Shwartz
- Nati Srebro
- John C. Duchi
- Yuchen Zhang
- L. Eon Bottou
- Zeyuan Allen-Zhu
- Rie Johnson
Who trusts Yossi Arjevani overall
- Jakub Konecný
- Jason D. Lee
- Waïss Azizian
- Sai Praneeth Karimireddy
- H. Brendan McMahan
- Sebastian U. Stich
- Blake E. Woodworth
- Jialei Wang
- Qihang Lin
- Lihua Lei
Papers from Yossi Arjevani's perspective
Ordered by how strongly the researchers Yossi Arjevani trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- Gradient-based learning applied to document recognition
- 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
- 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
- Communication Complexity of Distributed Convex Learning and Optimization (2015) — 225 citations
- Lower bounds for non-convex stochastic optimization (2019) — 476 citations
- A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates (2018) — 77 citations
- On Lower and Upper Bounds in Smooth and Strongly Convex Optimization (2016) — 41 citations