Shankar R. Rao
Computer Vision and Pattern Recognition · 2009–2010
A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 42 citations into it; #12,057 of 21,575 by trust here, #15,162 by citations
- Computational Mechanics — 35 citations into it; #4,305 of 10,001 by trust here, #4,450 by citations
- Signal Processing — 17 citations into it; #6,382 of 7,572 by trust here, #6,355 by citations
- Artificial Intelligence — 12 citations into it
- Computational Theory and Mathematics — 12 citations into it
- Numerical Analysis — 11 citations into it
- Statistics and Probability — 10 citations into it
- Statistical Learning Theory — 8 citations into it
Whom Shankar R. Rao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- David L. Donoho
- Qifa Ke
- René Vidal
- Fernando De la Torre
- Yi Ma
- Terence Tao
- Roberto Tron
- Jingyu Yan
- John Wright
Who trusts Shankar R. Rao overall
- René Vidal
- Ehsan Elhamifar
- Paolo Favaro
- Zhouchen Lin
- Guangcan Liu
- Chong You
- Muhamad Risqi U. Saputra
- Chris Russell
- Han Hu
- Daniel P. Robinson
Papers from Shankar R. Rao's perspective
Ordered by how strongly the researchers Shankar R. Rao 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
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories (2010) — 367 citations
- Segmentation of Natural Images by Texture and Boundary Compression (2010)
- Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization (2009) — 1,441 citations
- Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices (2009) — 363 citations