Yue Shi
Information Systems · 2010–2017
A researcher in the Science corpus: 9 papers; trusts 143 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 180 citations into it; #1,350 of 8,771 by trust here, #924 by citations
- Artificial Intelligence — 127 citations into it; #19,288 of 35,345 by trust here, #12,580 by citations
- Computer Vision and Pattern Recognition — 81 citations into it
- Recommender Systems — 68 citations into it
- Management Science and Operations Research — 66 citations into it; #4,476 of 11,946 by trust here, #2,355 by citations
- Marketing — 34 citations into it
- Signal Processing — 30 citations into it
- Statistical and Nonlinear Physics — 30 citations into it
Whom Yue Shi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yehuda Koren
- Thomas Hofmann
- Ruslan Salakhutdinov
- Steffen Rendle
- Geoffrey E. Hinton
- Jonathan L. Herlocker
- Diederik P. Kingma
- Andriy Mnih
- Mukund Deshpande
- Yoshua Bengio
Who trusts Yue Shi overall
- Harald Steck
- Alexandros Karatzoglou
- Zhaochun Ren
- Marius Kaminskas
- Weike Pan
- Weinan Zhang
- Piji Li
- Hao Wang
- Balázs Hidasi
- Yao Wu
Papers from Yue Shi's perspective
Ordered by how strongly the researchers Yue Shi 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering (2012) — 339 citations
- On Sampling Strategies for Neural Network-based Collaborative Filtering (2017) — 258 citations
- TFMAP: optimizing MAP for top-n context-aware recommendation (2012) — 231 citations
- Collaborative Filtering beyond the User-Item Matrix (2014) — 858 citations
- Returning is Believing: Optimizing Long-term User Engagement in Recommender Systems (2017) — 88 citations
- Mining contextual movie similarity with matrix factorization for context-aware recommendation (2013) — 111 citations
- Learning to rank for recommender systems (2013) — 154 citations
- Joint Text Embedding for Personalized Content-based Recommendation (2017) — 31 citations
- List-wise learning to rank with matrix factorization for collaborative filtering (2010) — 266 citations