Qingyao Ai
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 8 papers; trusts 213 researchers and is trusted by 63 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 214 citations into it; #3,149 of 35,345 by trust here, #4,080 by citations
- Information Systems — 123 citations into it; #1,441 of 8,771 by trust here, #869 by citations
- Natural Language Processing — 118 citations into it
- Computer Vision and Pattern Recognition — 68 citations into it; #11,070 of 21,575 by trust here, #10,905 by citations
- Information Retrieval & Search — 66 citations into it; #118 of 1,022 by trust here, #174 by citations
- Representation & Self-Supervised Learning — 49 citations into it
- Recommender Systems — 25 citations into it
- Evaluation & Benchmarks — 17 citations into it
Whom Qingyao Ai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Julian McAuley
- Geoffrey E. Hinton
- Yoshua Bengio
- Quoc V. Le
- Ilya Sutskever
- W. Bruce Croft
- Antoine Bordes
- Alex Krizhevsky
- Diederik P. Kingma
Who trusts Qingyao Ai overall
- Yongfeng Zhang
- Xu Chen
- Zhuyun Dai
- Xiang Wang
- Chenyan Xiong
- Xiangnan He
- Sean MacAvaney
- Jamie Callan
- Hamed Zamani
- Yikun Xian
Papers from Qingyao Ai's perspective
Ordered by how strongly the researchers Qingyao Ai trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- A Deep Relevance Matching Model for Ad-hoc Retrieval (2016) — 944 citations
- A Deep Look into Neural Ranking Models for Information Retrieval (2019) — 386 citations
- Explainable Product Search with a Dynamic Relation Embedding Model (2019) — 61 citations
- Towards Conversational Search and Recommendation: System Ask, User Respond (2018) — 451 citations
- Learning over Knowledge-Base Embeddings for Recommendation (2018) — 379 citations
- Joint Representation Learning for Top-N Recommendation with Heterogeneous Information Sources (2017) — 332 citations
- Analysis of the Paragraph Vector Model for Information Retrieval (2016) — 84 citations
- Semantic Matching by Non-Linear Word Transportation for Information Retrieval (2016) — 77 citations