Haihao Lu
Artificial Intelligence · 2016–2017
A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 16 citations into it; #17,839 of 35,345 by trust here, #22,463 by citations
- Optimization & Training — 11 citations into it; #2,556 of 2,601 by trust here, #2,313 by citations
- Computational Mechanics — 10 citations into it; #4,806 of 10,001 by trust here, #5,350 by citations
- Computational Theory and Mathematics — 6 citations into it
- Numerical Analysis — 6 citations into it; #3,511 of 3,586 by trust here, #2,242 by citations
Whom Haihao Lu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yurii E. Nesterov
- Kenji Kawaguchi
- Constantin Zalinescu
- Zi Wang
- Hrushikesh Narhar Mhaskar
- Bolei Zhou
- Rong Ge
- Tomaso A. Poggio
- Geoffrey E. Hinton
- Yoshua Bengio
Who trusts Haihao Lu overall
- Hongyang Zhang
- Thomas Kerdreux
- Yair Carmon
- Ryan D'Orazio
- Thomas Laurent
- Ohad Shamir
- Javier F. Peña
- Junru Shao
- Simon Shaolei Du
- Nicolas Loizou
Papers from Haihao Lu's perspective
Ordered by how strongly the researchers Haihao Lu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document 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
- 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)
- ImageNet: A large-scale hierarchical image database
Their papers
- Depth Creates No Bad Local Minima (2017) — 128 citations
- Relatively Smooth Convex Optimization by First-Order Methods, and Applications (2016) — 425 citations