Yiqun Liu
Artificial Intelligence · 2013–2022
A researcher in the Science corpus: 22 papers; trusts 252 researchers and is trusted by 36 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 247 citations into it; #5,657 of 35,345 by trust here, #4,682 by citations
- Information Systems — 184 citations into it; #727 of 8,771 by trust here, #391 by citations
- Computer Vision and Pattern Recognition — 107 citations into it
- Information Retrieval & Search — 103 citations into it
- Natural Language Processing — 77 citations into it
- Management Science and Operations Research — 50 citations into it; #11,065 of 11,946 by trust here, #8,906 by citations
- Recommender Systems — 48 citations into it
- Representation & Self-Supervised Learning — 34 citations into it
Whom Yiqun Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ruslan Salakhutdinov
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Yehuda Koren
- Kyunghyun Cho
- Kaiming He
Who trusts Yiqun Liu overall
- Yongfeng Zhang
- Xu Chen
- Chenyan Xiong
- Zhiyong Cheng
- Min Zhang
- Hanxiong Chen
- Xiangnan He
- Wayne Xin Zhao
- Chenliang Li
- Jingtao Zhan
Papers from Yiqun Liu's perspective
Ordered by how strongly the researchers Yiqun Liu 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Optimizing Dense Retrieval Model Training with Hard Negatives (2021) — 352 citations
- Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance (2021) — 97 citations
- Explicit factor models for explainable recommendation based on phrase-level sentiment analysis (2014) — 858 citations
- Temporal Relational Ranking for Stock Prediction (2018) — 545 citations
- Localized matrix factorization for recommendation based on matrix block diagonal forms (2013) — 78 citations
- Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables (2014) — 18 citations
- A Survey on the Fairness of Recommender Systems (2022) — 456 citations
- An Analysis of BERT in Document Ranking (2020) — 55 citations
- Leveraging Passage-level Cumulative Gain for Document Ranking (2020) — 40 citations
- RepBERT: Contextualized Text Embeddings for First-Stage Retrieval (2020) — 140 citations
- Preference-based Evaluation Metrics for Web Image Search (2020) — 14 citations
- Human Behavior Inspired Machine Reading Comprehension (2019) — 44 citations
- Jointly Learning Explainable Rules for Recommendation with Knowledge Graph (2019) — 246 citations
- Neural Attentional Rating Regression with Review-level Explanations (2018) — 644 citations
- SogouT-16: A New Web Corpus to Embrace IR Research (2017) — 14 citations
- Rating-Boosted Latent Topics: Understanding Users and Items with Ratings and Reviews (2016) — 174 citations
- Time-Aware Click Model (2016) — 42 citations
- Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis (2015) — 80 citations
- Predicting the popularity of web 2.0 items based on user comments (2014) — 112 citations
- Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification (2014) — 122 citations