Jin Kyu Kim
Artificial Intelligence · 2013–2014
A researcher in the Science corpus: 5 papers; trusts 12 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 40 citations into it; #34,318 of 35,345 by trust here, #11,192 by citations
- Optimization & Training — 26 citations into it
- Computer Networks and Communications — 19 citations into it
- Computer Vision and Pattern Recognition — 19 citations into it; #20,899 of 21,575 by trust here, #7,852 by citations
- Hardware and Architecture — 9 citations into it
- Natural Language Processing — 8 citations into it
Whom Jin Kyu Kim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Amr Ahmed
- Yucheng Low
- T. Griffiths
- Joseph E. Gonzalez
- Jerome H. Friedman
- David M. Blei
- Joseph K. Bradley
- Haifeng Yu
- Rainer Gemulla
- Alex Smola
Who trusts Jin Kyu Kim overall
- Henggang Cui
- Wei Dai
- Eric P. Xing
- Cong Xie
- Aaron Harlap
- Qirong Ho
- Aurick Qiao
- Mohammad Rostami
- Oluwasanmi Koyejo
- Jianyu Wang
Papers from Jin Kyu Kim's perspective
Ordered by how strongly the researchers Jin Kyu Kim 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
- Long Short-Term Memory
- Et al
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Petuum: A New Platform for Distributed Machine Learning on Big Data (2013) — 526 citations
- On Model Parallelization and Scheduling Strategies for Distributed Machine Learning (2014) — 129 citations
- Exploiting Bounded Staleness to Speed Up Big Data Analytics (2014) — 171 citations
- More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server (2013) — 813 citations
- Solving the Straggler Problem with Bounded Staleness (2013) — 149 citations