Xinhua Zhang
Artificial Intelligence · with Aslan · 2006–2014
A researcher in the Science corpus: 6 papers; trusts 116 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 55 citations into it; #16,798 of 35,345 by trust here, #23,731 by citations
- Computer Vision and Pattern Recognition — 34 citations into it
- Representation & Self-Supervised Learning — 24 citations into it
- Optimization & Training — 18 citations into it
- Probabilistic & Bayesian Methods — 17 citations into it; #936 of 1,525 by trust here, #1,136 by citations
- Statistical Learning Theory — 16 citations into it; #881 of 1,038 by trust here, #910 by citations
- Natural Language Processing — 14 citations into it
- Computational Mechanics — 11 citations into it
Whom Xinhua Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Alex Smola
- Michael I. Jordan
- Andrew Y. Ng
- Geoffrey E. Hinton
- Yoshua Bengio
- Bernhard Schölkopf
- Arthur Gretton
- Olivier Chapelle
- Avrim Blum
Who trusts Xinhua Zhang overall
- Krikamol Muandet
- Kenji Fukumizu
- Hongwei Wang
- Chuong B. Do
- Bernhard Schölkopf
- Nishant A. Mehta
- Simon Lacoste-Julien
- Le Song
- Bharath K. Sriperumbudur
- Yuchen Zhang
Papers from Xinhua Zhang's perspective
Ordered by how strongly the researchers Xinhua Zhang 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Tailoring density estimation via reproducing kernel moment matching (2008) — 65 citations
- Accelerated training of max-margin Markov networks with kernels (2011) — 7 citations
- Convex Deep Learning via Normalized Kernels (2014) — 29 citations
- Convex Two-Layer Modeling (2013) — 12 citations
- Kernel Measures of Independence for non-iid Data (2008) — 34 citations
- Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms (2006) — 62 citations