Ji Ho Park

Artificial Intelligence · with Fung · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 64 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it; #3,739 of 35,345 by trust here, #6,468 by citations
• Natural Language Processing — 21 citations into it; #908 of 5,688 by trust here, #1,510 by citations
• Safety, Robustness & Interpretability — 15 citations into it; #664 of 2,251 by trust here, #782 by citations
• Communication — 6 citations into it

Whom Ji Ho Park trusts overall

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

1. Zeerak Talat
2. Diederik P. Kingma
3. Yann LeCun
4. Junbo Jake Zhao
5. Jimmy Ba
6. Armand Joulin
7. Svetlana Kiritchenko
8. Tomas Mikolov
9. Pinkesh Badjatiya
10. Geoffrey E. Hinton

Who trusts Ji Ho Park overall

1. Michael Castelle
2. Ziqi Zhang
3. Pushkar Mishra
4. David Robinson
5. Joni O. Salminen
6. Emily Sheng
7. Mladen Karan
8. Kanika Narang
9. Filip Klubicka
10. Maarten Sap

Papers from Ji Ho Park's perspective

Ordered by how strongly the researchers Ji Ho Park trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Reducing Gender Bias in Abusive Language Detection (2018) — 385 citations
• One-step and Two-step Classification for Abusive Language Detection on Twitter (2017) — 380 citations