Qiang Shen
Artificial Intelligence · IEEE transactions on fuzzy systems · 2001–2012
A researcher in the Science corpus: 7 papers; trusts 111 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 75 citations into it; #16,662 of 35,345 by trust here, #20,377 by citations
- Computational Theory and Mathematics — 39 citations into it; #998 of 12,182 by trust here, #2,351 by citations
- Probabilistic & Bayesian Methods — 27 citations into it
- Computer Vision and Pattern Recognition — 16 citations into it
- Information Systems — 15 citations into it; #631 of 8,771 by trust here, #2,145 by citations
- Statistics and Probability — 15 citations into it
- Management Science and Operations Research — 14 citations into it; #1,805 of 11,946 by trust here, #4,746 by citations
- Evaluation & Benchmarks — 12 citations into it
Whom Qiang Shen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Judea Pearl
- J. Ross Quinlan
- Richard Jensen
- David E. Heckerman
- Nir Friedman
- Gerard A. Salton
- Manoranjan Dash
- Adnan Darwiche
- William W. Cohen
- Michael I. Jordan
Who trusts Qiang Shen overall
- Richard Jensen
- Qinghua Hu
- Jianhua Dai
- Pradipta Maji
- Kai Keng Ang
- Ren-hong Diao
- Daren Yu
- Qing Xu
- Kuttiannan Thangavel
- Y. Qian
Papers from Qiang Shen's perspective
Ordered by how strongly the researchers Qiang Shen 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)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- 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
- Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches (2004) — 696 citations
- Fuzzy-Rough Sets Assisted Attribute Selection (2007) — 441 citations
- Rough set-aided keyword reduction for text categorization (2001) — 307 citations
- New Approaches to Fuzzy-Rough Feature Selection (2009) — 566 citations
- Learning Bayesian networks: approaches and issues (2011) — 355 citations
- Feature Selection With Harmony Search (2012) — 168 citations
- Computational Intelligence and Feature Selection - Rough and Fuzzy Approaches (2008) — 349 citations