Amirhossein Reisizadeh
Computer Networks and Communications · 2017–2019
A researcher in the Science corpus: 7 papers; trusts 67 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 143 citations into it; #4,149 of 9,886 by trust here, #2,358 by citations
- Artificial Intelligence — 107 citations into it; #13,819 of 35,345 by trust here, #9,641 by citations
- Optimization & Training — 79 citations into it; #1,750 of 2,601 by trust here, #1,766 by citations
- Computational Mechanics — 46 citations into it
- ML Systems & Hardware — 44 citations into it
- Federated & Distributed Learning — 25 citations into it; #292 of 319 by trust here, #190 by citations
- Electrical and Electronic Engineering — 21 citations into it
- Information Systems — 20 citations into it
Whom Amirhossein Reisizadeh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Angelia Nedić
- Michael G. Rabbat
- John C. Duchi
- Aryan Mokhtari
- David John Cameron MacKay
- John N. Tsitsiklis
- Wei Shi
- Qing Ling
- Konstantinos I. Tsianos
- Kun Yuan
Who trusts Amirhossein Reisizadeh overall
- Aryan Mokhtari
- Zachary B. Charles
- Ahmed Khaled
- Thinh T. Doan
- Tian Li
- Ramtin Pedarsani
- Hamed Hassani
- Alireza Fallah
- Albert S. Berahas
- Songze Li
Papers from Amirhossein Reisizadeh's perspective
Ordered by how strongly the researchers Amirhossein Reisizadeh 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
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- 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)
Their papers
- FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization (2019) — 974 citations
- Robust and Communication-Efficient Collaborative Learning (2019) — 98 citations
- CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning (2019) — 30 citations
- Coded Computation Over Heterogeneous Clusters (2019) — 21 citations
- Quantized Decentralized Consensus Optimization (2018) — 30 citations
- An Exact Quantized Decentralized Gradient Descent Algorithm (2018) — 139 citations
- Coded computation over heterogeneous clusters (2017) — 246 citations