Kevin Small

Artificial Intelligence · 2009–2019

A researcher in the Science corpus: 6 papers; trusts 110 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it; #16,078 of 35,345 by trust here, #13,544 by citations
• Natural Language Processing — 41 citations into it; #4,065 of 5,688 by trust here, #4,361 by citations
• Reinforcement Learning — 15 citations into it
• Evaluation & Benchmarks — 11 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Model Architectures — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Kevin Small trusts overall

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

1. Omar Zaidan
2. Thorsten Joachims
3. Yoshua Bengio
4. Diederik P. Kingma
5. Burr Settles
6. Geoffrey E. Hinton
7. Ronald J. Williams
8. Michael Collins
9. Jason Eisner
10. Sugato Basu

Who trusts Kevin Small overall

1. Stefano Teso
2. Byron C. Wallace
3. Peter Hase
4. Alison O'Mara-Eves
5. Ye Zhang
6. Iain James Marshall
7. Kristian Kersting
8. Xin He
9. Patrick Schramowski
10. Mohit Bansal

Papers from Kevin Small's perspective

Ordered by how strongly the researchers Kevin Small 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• End-to-End Offline Goal-Oriented Dialog Policy Learning via Policy Gradient (2017) — 43 citations
• Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering (2019) — 92 citations
• Interactive Feature Space Construction using Semantic Information (2009) — 24 citations
• Deploying an interactive machine learning system in an evidence-based practice center: abstrackr (2012) — 611 citations
• The Constrained Weight Space SVM: Learning with Ranked Features (2011) — 45 citations
• Class Imbalance, Redux (2011) — 227 citations