Sean F. Lawlor
Computer Networks and Communications · 2012
A researcher in the Science corpus: 3 papers; trusts 28 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 29 citations into it; #587 of 9,886 by trust here, #1,192 by citations
- Artificial Intelligence — 22 citations into it; #19,760 of 35,345 by trust here, #20,377 by citations
- Optimization & Training — 16 citations into it
- Computational Mechanics — 10 citations into it; #977 of 10,001 by trust here, #1,816 by citations
- Statistical and Nonlinear Physics — 8 citations into it
- ML Systems & Hardware — 7 citations into it
- Algorithms & Complexity — 5 citations into it
Whom Sean F. Lawlor trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- John C. Duchi
- Alekh Agarwal
- Konstantinos I. Tsianos
- Eugene Seneta
- Angelia Nedić
- Muthu Dayalan
- Behrouz Touri
- Michael G. Rabbat
- Yurii E. Nesterov
- Shai Shalev-Shwartz
Who trusts Sean F. Lawlor overall
- Angelia Nedić
- Aryan Mokhtari
- Konstantinos I. Tsianos
- Amirhossein Reisizadeh
- Soomin Lee
- Michael G. Rabbat
- Thinh T. Doan
- Alexander Olshevsky
- Albert S. Berahas
- Kun Yuan
Papers from Sean F. Lawlor's perspective
Ordered by how strongly the researchers Sean F. Lawlor 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
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
Their papers
- Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization (2012) — 84 citations
- Consensus-based distributed optimization: Practical issues and applications in large-scale machine learning (2012) — 249 citations
- Push-Sum Distributed Dual Averaging for convex optimization (2012) — 326 citations