Jennifer Gillenwater

Artificial Intelligence · 2010–2020

A researcher in the Science corpus: 4 papers; trusts 70 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it; #8,334 of 35,345 by trust here, #10,207 by citations
• Optimization & Training — 19 citations into it
• Natural Language Processing — 18 citations into it
• Federated & Distributed Learning — 13 citations into it
• Statistics and Probability — 10 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Molecular Biology — 7 citations into it

Whom Jennifer Gillenwater trusts overall

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

1. Alex Kulesza
2. B. Taskar
3. Moran Feldman
4. Alex Krizhevsky
5. Andrew McCallum
6. Jan Vondr'ak
7. Boris Polyak
8. Geoffrey E. Hinton
9. Joseph (Seffi) Naor
10. Günes Erkan

Who trusts Jennifer Gillenwater overall

1. Alex Kulesza
2. B. Taskar
3. Boqing Gong
4. Laming Chen
5. Jin-ge Yao
6. Kevin Gimpel
7. Donghoon Lee
8. Shashank Srivastava
9. Jianfeng Gao
10. Wei-Lun Chao

Papers from Jennifer Gillenwater's perspective

Ordered by how strongly the researchers Jennifer Gillenwater 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Posterior Regularization for Structured Latent Variable Models (2010) — 573 citations
• Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms (2020) — 129 citations
• Near-Optimal MAP Inference for Determinantal Point Processes (2012) — 157 citations
• Discovering Diverse and Salient Threads in Document Collections (2012) — 90 citations