Ramtin Pedarsani
Computer Networks and Communications · 2013–2019
A researcher in the Science corpus: 11 papers; trusts 80 researchers and is trusted by 38 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 176 citations into it; #847 of 9,886 by trust here, #774 by citations
- Artificial Intelligence — 116 citations into it; #5,464 of 35,345 by trust here, #5,970 by citations
- Optimization & Training — 91 citations into it; #1,751 of 2,601 by trust here, #1,766 by citations
- Computational Mechanics — 53 citations into it
- ML Systems & Hardware — 44 citations into it; #96 of 575 by trust here, #236 by citations
- Information Systems — 29 citations into it
- Electrical and Electronic Engineering — 27 citations into it
- Computer Vision and Pattern Recognition — 26 citations into it
Whom Ramtin Pedarsani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mohammad Ali Maddah-Ali
- Angelia Nedić
- Urs Niesen
- Michael G. Rabbat
- David John Cameron MacKay
- Pravin Pratap Varaiya
- Amirhossein Reisizadeh
- Joseph Dean
- John C. Duchi
- John N. Tsitsiklis
Who trusts Ramtin Pedarsani overall
- Amirhossein Reisizadeh
- Qian Yu
- Mohammad Ali Maddah-Ali
- Zachary B. Charles
- Deepesh Data
- Amir Salman Avestimehr
- Sanghamitra Dutta
- Can Bülent Karakus
- Aryan Mokhtari
- Songze Li
Papers from Ramtin Pedarsani's perspective
Ordered by how strongly the researchers Ramtin Pedarsani 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)
- ImageNet Large Scale Visual Recognition Challenge
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
- Analysis of fixed-time control☆ (2014) — 78 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
- Speeding Up Distributed Machine Learning Using Codes (2015) — 924 citations
- Platoons of connected vehicles can double throughput in urban roads (2015) — 375 citations
- Online Coded Caching (2013) — 315 citations