Dingding Wang
Artificial Intelligence · 2008–2018
A researcher in the Science corpus: 4 papers; trusts 60 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 61 citations into it; #18,790 of 35,345 by trust here, #23,731 by citations
- Natural Language Processing — 37 citations into it
- Representation & Self-Supervised Learning — 24 citations into it
- Computer Vision and Pattern Recognition — 23 citations into it
- Information Systems — 23 citations into it
- Model Architectures — 9 citations into it
- Signal Processing — 7 citations into it
- Management Science and Operations Research — 6 citations into it; #10,744 of 11,946 by trust here, #7,638 by citations
Whom Dingding Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Quoc V. Le
- Tomas Mikolov
- Alex Krizhevsky
- Yann LeCun
- Andrew Y. Ng
- Richard Socher
- Radford M. Neal
- Ilya Sutskever
Who trusts Dingding Wang overall
- A. Ozbayoglu
- Rasim M. Alguliyev
- Dogu Araci
- M. Ugur Gudelek
- Ramiz M. Aliguliyev
- Nhan Cach Dang
- Hanjie Chen
- Mozhgan Karimi
- Omer Berat Sezer
Papers from Dingding Wang's perspective
Ordered by how strongly the researchers Dingding Wang 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)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Big Data: Deep Learning for financial sentiment analysis (2018) — 347 citations
- SCENE: a scalable two-stage personalized news recommendation system (2011) — 253 citations
- Finding Expert Authors in Financial Forum Using Deep Learning Methods (2018) — 12 citations
- Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization (2008) — 345 citations