Yucheng Low
Computer Networks and Communications · 2009–2012
A researcher in the Science corpus: 9 papers; trusts 42 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 39 citations into it; #6,512 of 9,886 by trust here, #3,005 by citations
- Artificial Intelligence — 35 citations into it; #12,707 of 35,345 by trust here, #12,244 by citations
- Computer Vision and Pattern Recognition — 26 citations into it; #21,315 of 21,575 by trust here, #8,612 by citations
- Information Systems — 25 citations into it; #5,167 of 8,771 by trust here, #1,778 by citations
- Probabilistic & Bayesian Methods — 24 citations into it; #807 of 1,525 by trust here, #1,031 by citations
- Statistical and Nonlinear Physics — 16 citations into it
- ML Systems & Hardware — 15 citations into it; #480 of 575 by trust here, #177 by citations
- Hardware and Architecture — 14 citations into it; #1,524 of 1,551 by trust here, #318 by citations
Whom Yucheng Low trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Muthu Dayalan
- Joseph E. Gonzalez
- Dimitri P. Bertsekas
- Gal Elidan
- T. Griffiths
- Alex Smola
- U. Kang
- Ruslan Salakhutdinov
- Robert Tibshirani
- Geoffrey E. Hinton
Who trusts Yucheng Low overall
- Eric P. Xing
- Joseph E. Gonzalez
- Qirong Ho
- Le Song
- Mu Li
- Wei Dai
- Aaron Harlap
- Hyokun Yun
- Aapo Kyrola
- Carlos Guestrin
Papers from Yucheng Low's perspective
Ordered by how strongly the researchers Yucheng Low 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- Distributed GraphLab: A Framework for Machine Learning in the Cloud (2012) — 1,087 citations
- GraphLab: A New Framework For Parallel Machine Learning (2010) — 927 citations
- Kernel Belief Propagation (2011) — 86 citations
- PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs (2012) — 2,018 citations
- Distributed GraphLab: A Framework for Machine Learning in the Cloud (2012) — 687 citations
- GraphLab: A Distributed Framework for Machine Learning in the Cloud (2011) — 24 citations
- Multiple domain user personalization (2011) — 36 citations
- GraphLab: A New Parallel Framework for Machine Learning (2010) — 471 citations
- Residual Splash for Optimally Parallelizing Belief Propagation (2009) — 141 citations