Dennis Wei
Artificial Intelligence · with Varshney · 2014–2021
A researcher in the Science corpus: 10 papers; trusts 63 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 166 citations into it; #11,172 of 35,345 by trust here, #7,413 by citations
- Safety, Robustness & Interpretability — 80 citations into it
- Safety Research — 33 citations into it
- AI Ethics, Fairness & Society — 32 citations into it; #223 of 494 by trust here, #118 by citations
- Natural Language Processing — 31 citations into it
- Computer Vision and Pattern Recognition — 30 citations into it
- Information Systems — 24 citations into it
- Statistical Learning Theory — 23 citations into it
Whom Dennis Wei trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Toon Calders
- Faisal Kamiran
- William W. Cohen
- Neil D. Lawrence
- Kush R. Varshney
- Charles Bouveyron
- R. Rivest
- Tong Wang
- Geoffrey E. Hinton
- Cynthia Rudin
Who trusts Dennis Wei overall
- Kush R. Varshney
- Cynthia Rudin
- Silvia Chiappa
- Dana Pessach
- Luca Oneto
- Pantelis Linardatos
- Nadia Burkart
- Amit Dhurandhar
- Giulia Vilone
- Murat Firat
Papers from Dennis Wei's perspective
Ordered by how strongly the researchers Dennis Wei 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Optimized Data Pre-Processing for Discrimination Prevention (2017) — 64 citations
- Your fairness may vary: Pretrained language model fairness in toxic text classification (2021) — 61 citations
- Learning sparse two-level boolean rules (2016) — 31 citations
- Fair Transfer Learning with Missing Protected Attributes (2019) — 123 citations
- One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques (2019) — 478 citations
- TED: Teaching AI to Explain its Decisions (2018) — 115 citations
- Boolean Decision Rules via Column Generation (2018) — 200 citations
- Optimized Pre-Processing for Discrimination Prevention (2017) — 843 citations
- Interpretable Two-level Boolean Rule Learning for Classification (2015) — 55 citations
- Robust binary hypothesis testing under contaminated likelihoods (2014) — 4 citations