Keith B. Hall

Artificial Intelligence · 2003–2022

A researcher in the Science corpus: 11 papers; trusts 85 researchers and is trusted by 54 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 178 citations into it; #11,799 of 35,345 by trust here, #4,080 by citations
• Natural Language Processing — 103 citations into it
• Information Retrieval & Search — 73 citations into it; #1,000 of 1,022 by trust here, #340 by citations
• Computer Vision and Pattern Recognition — 59 citations into it
• Evaluation & Benchmarks — 29 citations into it
• Information Systems — 21 citations into it
• Model Architectures — 13 citations into it
• Optimization & Training — 11 citations into it

Whom Keith B. Hall trusts overall

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

1. Richard S. Sutton
2. Michael Collins
3. Yoav Freund
4. Geoffrey E. Hinton
5. Michael L. Littman
6. Diederik P. Kingma
7. Yoshua Bengio
8. Ryan T. McDonald
9. Fernando C Pereira
10. Michael H. Bowling

Who trusts Keith B. Hall overall

1. Ergun Biçici
2. Michael H. Bowling
3. Tao Zhang
4. Matthew J. Hausknecht
5. Farzin Haddadpour
6. Hao Yu
7. Katja Filippova
8. John C. Duchi
9. Kumar Kshitij Patel
10. Aymeric Dieuleveut

Papers from Keith B. Hall's perspective

Ordered by how strongly the researchers Keith B. Hall 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Long Short-Term Memory
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
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

• A Study on Similarity and Relatedness Using Distributional and WordNet-based Approaches (2009) — 985 citations
• Large Dual Encoders Are Generalizable Retrievers (2021) — 644 citations
• Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models (2021) — 830 citations
• Encoding linear models as weighted finite-state transducers (2014) — 26 citations
• Composition-based on-the-fly rescoring for salient n-gram biasing (2015) — 76 citations
• Promptagator: Few-shot Dense Retrieval From 8 Examples (2022) — 350 citations
• Zero-shot Neural Retrieval via Domain-targeted Synthetic Query Generation (2020) — 32 citations
• Processing South Asian Languages Written in the Latin Script: the Dakshina Dataset (2020) — 94 citations
• Universal Dependency Annotation for Multilingual Parsing (2013) — 603 citations
• Distributed Training Strategies for the Structured Perceptron (2010) — 321 citations
• Correlated Q-Learning (2003) — 477 citations