Sumeet Singh

Artificial Intelligence · 2003–2019

A researcher in the Science corpus: 6 papers; trusts 26 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it; #17,254 of 35,345 by trust here, #17,776 by citations
• Computer Networks and Communications — 14 citations into it; #4,129 of 9,886 by trust here, #5,733 by citations
• Natural Language Processing — 13 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Management Science and Operations Research — 8 citations into it
• Hardware and Architecture — 7 citations into it; #569 of 1,551 by trust here, #908 by citations
• Control and Systems Engineering — 6 citations into it
• Reinforcement Learning — 6 citations into it

Whom Sumeet Singh trusts overall

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

1. Cristian Estan
2. George Varghese
3. Florin Baboescu
4. Andrew Y. Ng
5. Pieter Abbeel
6. David Moore
7. Philipp Koehn
8. Rico Sennrich
9. Nick G. Duffield
10. Sergey Levine

Who trusts Sumeet Singh overall

1. David E. Taylor
2. Simon Pak Ho Chung
3. Edith Cohen
4. Jonathan S. Turner
5. James Newsome
6. Nanxi Kang
7. Christopher Krügel
8. Aloysius Ka-Lau Mok
9. Carsten Lund
10. Ke Wang

Papers from Sumeet Singh's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models (2017) — 72 citations
• Improving Robustness of Machine Translation with Synthetic Noise (2019) — 89 citations
• A review on the improvement of stevia [Stevia rebaudiana (Bertoni)] (2011) — 377 citations
• Automated Worm Fingerprinting (2004) — 614 citations
• Packet classification using multidimensional cutting (2003) — 606 citations
• Packet classification for core routers: is there an alternative to CAMs? (2003) — 299 citations