Karan Singh

Artificial Intelligence · with Zhang · 2017–2018

A researcher in the Science corpus: 6 papers; trusts 45 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it; #28,495 of 35,345 by trust here, #17,110 by citations
• Optimization & Training — 39 citations into it
• Reinforcement Learning — 39 citations into it; #1,938 of 2,242 by trust here, #1,895 by citations
• Management Science and Operations Research — 27 citations into it; #9,489 of 11,946 by trust here, #4,921 by citations
• Computer Networks and Communications — 13 citations into it
• Statistical Learning Theory — 13 citations into it; #930 of 1,038 by trust here, #893 by citations
• Computational Mechanics — 10 citations into it; #6,660 of 10,001 by trust here, #3,463 by citations
• Computer Vision and Pattern Recognition — 8 citations into it; #20,089 of 21,575 by trust here, #16,367 by citations

Whom Karan Singh trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Elad Hazan
2. Shai Shalev-Shwartz
3. Martin A. Zinkevich
4. Sham M. Kakade
5. Sam T. Roweis
6. Cynthia Dwork
7. Nicolò Cesa-Bianchi
8. Geoffrey E. Hinton
9. Nick Littlestone
10. Richard S. Sutton

Who trusts Karan Singh overall

1. Samet Oymak
2. Zeyuan Allen-Zhu
3. Elad Hazan
4. Jakub Marecek
5. Abhimanyu Das

Papers from Karan Singh's perspective

Ordered by how strongly the researchers Karan Singh trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

Their papers

• Provably Efficient Maximum Entropy Exploration (2018) — 369 citations
• Learning Linear Dynamical Systems via Spectral Filtering (2017) — 122 citations
• The Case for Full-Matrix Adaptive Regularization (2018) — 21 citations
• Spectral Filtering for General Linear Dynamical Systems (2018) — 109 citations
• The Price of Differential Privacy for Online Learning (2017) — 109 citations
• Towards Provable Control for Unknown Linear Dynamical Systems (2018) — 39 citations