Seyoung Kim
Molecular Biology · with Xing · 2009–2010
A researcher in the Science corpus: 4 papers; trusts 45 researchers and is trusted by 66 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 30 citations into it; #7,811 of 17,773 by trust here, #15,531 by citations
- Statistics and Probability — 29 citations into it; #997 of 12,932 by trust here, #1,650 by citations
- Genetics — 24 citations into it; #130 of 6,854 by trust here, #1,264 by citations
- Artificial Intelligence — 14 citations into it
- Optimization & Training — 12 citations into it; #447 of 2,601 by trust here, #924 by citations
- Computational Mechanics — 11 citations into it
- Computer Vision and Pattern Recognition — 8 citations into it
- Control and Systems Engineering — 5 citations into it
Whom Seyoung Kim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert Tibshirani
- Francis R. Bach
- Eric R. Ziegel
- Trevor J. Hastie
- Jerome H. Friedman
- Bin Zhang
- Andrew Y. Ng
- Michael Olivier
- Sanford Weisberg
- Peng Zhao
Who trusts Seyoung Kim overall
- Francis R. Bach
- Lei Han
- Rodolphe Jenatton
- Yu Zhang
- Joelle Pineau
- Jun Liu
- Jieping Ye
- Jiliang Tang
- Qiang Yang
- Yu Zhang
Papers from Seyoung Kim's perspective
Ordered by how strongly the researchers Seyoung Kim 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
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Regression Shrinkage and Selection via the Lasso
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity (2009) — 478 citations
- Multi-population GWA mapping via multi-task regularized regression (2010) — 78 citations
- Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso (2010) — 111 citations
- Statistical Estimation of Correlated Genome Associations to a Quantitative Trait Network (2009) — 250 citations