Davood Hajinezhad
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 3 papers; trusts 272 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 126 citations into it; #12,104 of 35,345 by trust here, #20,377 by citations
- Reinforcement Learning — 88 citations into it
- Computer Networks and Communications — 34 citations into it; #4,489 of 9,886 by trust here, #7,492 by citations
- Computational Mechanics — 28 citations into it; #4,002 of 10,001 by trust here, #6,582 by citations
- Computational Theory and Mathematics — 26 citations into it; #7,278 of 12,182 by trust here, #7,851 by citations
- Computer Vision and Pattern Recognition — 25 citations into it
- Optimization & Training — 20 citations into it
- Control and Systems Engineering — 18 citations into it
Whom Davood Hajinezhad trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Dimitri P. Bertsekas
- Geoffrey E. Hinton
- Ronald J. Williams
- Yoshua Bengio
- Alex Krizhevsky
- Diederik P. Kingma
- Yann LeCun
- Karen Simonyan
- Andrew Barto
Who trusts Davood Hajinezhad overall
Papers from Davood Hajinezhad's perspective
Ordered by how strongly the researchers Davood Hajinezhad 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
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- 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
- A review of cooperative multi-agent deep reinforcement learning (2019) — 635 citations
- Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks (2017) — 169 citations
- NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization (2016) — 45 citations