Ya Xue
Artificial Intelligence · 2005–2008
A researcher in the Science corpus: 5 papers; trusts 38 researchers and is trusted by 68 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 32 citations into it; #13,129 of 35,345 by trust here, #15,866 by citations
- Statistics and Probability — 25 citations into it; #5,624 of 12,932 by trust here, #7,508 by citations
- Statistical Learning Theory — 8 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Computer Vision and Pattern Recognition — 7 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it; #361 of 1,525 by trust here, #273 by citations
- Computational Mechanics — 6 citations into it; #1,659 of 10,001 by trust here, #3,190 by citations
- Signal Processing — 5 citations into it; #1,234 of 7,572 by trust here, #2,525 by citations
Whom Ya Xue trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michael I. Jordan
- Peter Müller
- David John Cameron MacKay
- Hemant Ishwaran
- Radford M. Neal
- Geoffrey E. Hinton
- Zoubin Ghahramani
- Tommi S. Jaakkola
- Jim Albert
- David L. Donoho
Who trusts Ya Xue overall
- Yu Zhang
- Yu Zhang
- Qiang Yang
- Lawrence Carin
- Hal Daumé Iii
- Mohammad Rostami
- Jiayu Zhou
- Yongxin Yang
- Xuejun Liao
- Dit-Yan Yeung
Papers from Ya Xue's perspective
Ordered by how strongly the researchers Ya Xue 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
- Long Short-Term Memory
- 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
- Logistic regression with an auxiliary data source (2005) — 226 citations
- The Matrix Stick-Breaking Process (2008) — 47 citations
- The matrix stick-breaking process for flexible multi-task learning (2007) — 28 citations
- Bayesian Compressive Sensing (2008) — 2,366 citations
- Multi-Task Learning for Classification with Dirichlet Process Priors (2007) — 621 citations