Haoruo Peng
Natural Language Processing · 2015–2019
A researcher in the Science corpus: 6 papers; trusts 132 researchers and is trusted by 32 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 95 citations into it; #1,712 of 5,688 by trust here, #3,235 by citations
- Artificial Intelligence — 83 citations into it; #7,301 of 35,345 by trust here, #14,718 by citations
- Computer Vision and Pattern Recognition — 15 citations into it
- Evaluation & Benchmarks — 11 citations into it
- Information Systems — 9 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
- Information Extraction — 7 citations into it
- Management Science and Operations Research — 7 citations into it; #9,217 of 11,946 by trust here, #9,383 by citations
Whom Haoruo Peng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michael Collins
- Dan Roth
- Tomas Mikolov
- Xiaoqiang Luo
- Wen-tau Yih
- Ronald J. Williams
- Geoffrey E. Hinton
- Vincent Ng
- Yoshua Bengio
- Ilya Sutskever
Who trusts Haoruo Peng overall
- Artem Abzaliev
- Jieyu Zhao
- Ali Emami
- Carolin (Haas) Lawrence
- Trieu H. Trinh
- Juri Opitz
- Keisuke Sakaguchi
- Mohit Iyyer
- Xiaodong Yu
- Tianlu Wang
Papers from Haoruo Peng's perspective
Ordered by how strongly the researchers Haoruo Peng 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Solving Hard Coreference Problems (2019) — 90 citations
- Event Detection and Co-reference with Minimal Supervision (2016) — 113 citations
- Story Comprehension for Predicting What Happens Next (2017) — 109 citations
- Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision (2017) — 20 citations
- Regions, Periods, Activities: Uncovering Urban Dynamics via Cross-Modal Representation Learning (2017) — 151 citations
- The University of Illinois submission to the WMT 2015 Shared Translation Task (2015)