Amir Salman Avestimehr

Artificial Intelligence · 2009–2021

A researcher in the Science corpus: 25 papers; trusts 460 researchers and is trusted by 60 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 334 citations into it; #3,310 of 35,345 by trust here, #3,842 by citations
Computer Networks and Communications — 143 citations into it; #426 of 9,886 by trust here, #578 by citations
Optimization & Training — 116 citations into it
Computer Vision and Pattern Recognition — 104 citations into it
Federated & Distributed Learning — 91 citations into it; #131 of 319 by trust here, #158 by citations
ML Systems & Hardware — 76 citations into it; #105 of 575 by trust here, #210 by citations
Privacy & Security — 73 citations into it; #486 of 709 by trust here, #462 by citations
Efficiency & Compression — 61 citations into it

Whom Amir Salman Avestimehr trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Amir Salman Avestimehr overall

Papers from Amir Salman Avestimehr's perspective

Ordered by how strongly the researchers Amir Salman Avestimehr 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)
Gradient-based learning applied to document recognition
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
ImageNet: A large-scale hierarchical image database
Long Short-Term Memory
Learning Multiple Layers of Features from Tiny Images
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

Coded Computing for Federated Learning at the Edge (2020) — 11 citations
Lagrange Coded Computing: Optimal Design for Resiliency, Security and Privacy (2018) — 461 citations
Wireless Network Information Flow: A Deterministic Approach (2009) — 883 citations
Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication (2017) — 511 citations
FairFed: Enabling Group Fairness in Federated Learning (2021) — 324 citations
FedNAS: Federated Deep Learning via Neural Architecture Search (2020) — 98 citations
Secure Aggregation with Heterogeneous Quantization in Federated Learning (2020) — 29 citations
Mitigating Byzantine Attacks in Federated Learning (2020) — 44 citations
Group Knowledge Transfer: Collaborative Training of Large CNNs on the Edge (2020) — 24 citations
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning (2020) — 387 citations
A Scalable Approach for Privacy-Preserving Collaborative Machine Learning (2020) — 57 citations
Byzantine-Resilient Secure Federated Learning (2020) — 330 citations
CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning (2019) — 30 citations
CodedPrivateML: A Fast and Privacy-Preserving Framework for Distributed Machine Learning (2019) — 133 citations
Coded Computation Over Heterogeneous Clusters (2019) — 21 citations
Polynomially Coded Regression: Optimal Straggler Mitigation via Data Encoding (2018) — 49 citations
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training (2018) — 70 citations
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training (2018) — 112 citations
Straggler Mitigation in Distributed Matrix Multiplication: Fundamental Limits and Optimal Coding (2018) — 314 citations
Coded TeraSort (2017) — 54 citations