Naman Agarwal

Optimization & Training · 2016–2022

A researcher in the Science corpus: 9 papers; trusts 79 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

Whom Naman Agarwal trusts overall

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

  1. James Martens
  2. Yurii E. Nesterov
  3. Shai Shalev-Shwartz
  4. Elad Hazan
  5. John C. Duchi
  6. Tong Zhang
  7. Cynthia Dwork
  8. Geoffrey E. Hinton
  9. Rie Johnson
  10. Donald Goldfarb

Who trusts Naman Agarwal overall

  1. Pang Wei Koh
  2. Raghu Bollapragada
  3. Albert S. Berahas
  4. Percy Liang
  5. Sai Praneeth Karimireddy
  6. Sidak Pal Singh
  7. Ryan P. Adams
  8. Peter Kairouz
  9. Jorge Nocedal
  10. Haishan Ye

Papers from Naman Agarwal's perspective

Ordered by how strongly the researchers Naman Agarwal 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. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers