Huda Khayrallah

Natural Language Processing · 2016–2019

A researcher in the Science corpus: 8 papers; trusts 162 researchers and is trusted by 33 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 127 citations into it; #1,218 of 5,688 by trust here, #2,045 by citations
• Artificial Intelligence — 126 citations into it; #4,794 of 35,345 by trust here, #7,010 by citations
• Computer Vision and Pattern Recognition — 56 citations into it; #5,281 of 21,575 by trust here, #7,027 by citations
• Optimization & Training — 23 citations into it
• Evaluation & Benchmarks — 22 citations into it; #1,192 of 3,147 by trust here, #2,330 by citations
• Model Architectures — 15 citations into it
• Machine Translation — 13 citations into it; #161 of 292 by trust here, #175 by citations
• Language and Linguistics — 8 citations into it

Whom Huda Khayrallah trusts overall

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

1. Philipp Koehn
2. Jörg Tiedemann
3. Rico Sennrich
4. Kenneth Heafield
5. Yoshua Bengio
6. Barry Haddow
7. Dzmitry Bahdanau
8. David Chiang
9. Geoffrey E. Hinton
10. Michel Galley

Who trusts Huda Khayrallah overall

1. Felix Stahlberg
2. Philipp Koehn
3. Brian Thompson
4. Marcin Junczys-Dowmunt
5. Vishrav Chaudhary
6. Shuhao Gu
7. Eleftheria Briakou
8. Danielle Saunders
9. Matt Post
10. Sorami Hisamoto

Papers from Huda Khayrallah's perspective

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

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

Their papers

• On the Impact of Various Types of Noise on Neural Machine Translation (2018) — 230 citations
• Findings of the WMT 2018 Shared Task on Parallel Corpus Filtering (2018) — 121 citations
• Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation (2019) — 146 citations
• The JHU Parallel Corpus Filtering Systems for WMT 2018 (2018) — 8 citations
• Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation (2018) — 56 citations
• The JHU Machine Translation Systems for WMT 2016 (2016) — 20 citations
• An Empirical Exploration of Curriculum Learning for Neural Machine Translation (2018) — 125 citations
• Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation (2018) — 64 citations