Kwang-Sung Jun

Artificial Intelligence · 2010–2018

A researcher in the Science corpus: 4 papers; trusts 12 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it; #30,853 of 35,345 by trust here, #25,809 by citations
• Management Science and Operations Research — 12 citations into it; #10,405 of 11,946 by trust here, #7,262 by citations
• Natural Language Processing — 8 citations into it; #2,972 of 5,688 by trust here, #3,826 by citations
• Reinforcement Learning — 8 citations into it

Whom Kwang-Sung Jun trusts overall

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

1. Nicolò Cesa-Bianchi
2. Peter Auer
3. Radford M. Neal
4. András György
5. Chih-Jen Lin
6. T. Griffiths
7. Gábor Lugosi
8. Geoffrey E. Hinton
9. Bo Pang
10. Andrew Y. Ng

Who trusts Kwang-Sung Jun overall

1. Ian Waudby-Smith
2. Mladen Karan
3. Lijun Zhang
4. Shervin Malmasi
5. Yawei Zhao
6. Joel Veness
7. Marcos Zampieri
8. Xiaojin Zhu
9. Aaditya Ramdas
10. Anna Schmidt

Papers from Kwang-Sung Jun's perspective

Ordered by how strongly the researchers Kwang-Sung Jun trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Improved Strongly Adaptive Online Learning using Coin Betting (2016) — 95 citations
• Adversarial Attacks on Stochastic Bandits (2018) — 139 citations
• Learning from Bullying Traces in Social Media (2012) — 413 citations
• Cognitive Models of Test-Item Effects in Human Category Learning (2010) — 29 citations