Lorenzo Orecchia

Artificial Intelligence · 2013–2018

A researcher in the Science corpus: 4 papers; trusts 30 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

Whom Lorenzo Orecchia trusts overall

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

  1. Yurii E. Nesterov
  2. Guanghui Lan
  3. Lin Xiao
  4. Daniel A. Spielman
  5. H. Brendan McMahan
  6. Elad Hazan
  7. Sanjeev Arora
  8. Zeyuan Allen-Zhu
  9. Saeed Ghadimi
  10. Ohad Shamir

Who trusts Lorenzo Orecchia overall

  1. Zeyuan Allen-Zhu
  2. Yin Tat Lee
  3. Sébastien Bubeck
  4. Mahmoud Assran
  5. Aaron Sidford
  6. Jason D. Lee
  7. Di Wang
  8. Alexandre d'Aspremont
  9. Walid Krichene
  10. Michael G. Rabbat

Papers from Lorenzo Orecchia's perspective

Ordered by how strongly the researchers Lorenzo Orecchia 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  6. Learning Multiple Layers of Features from Tiny Images
  7. ImageNet: A large-scale hierarchical image database
  8. Attention is All you Need (Neural Information Processing Systems)
  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