Alina Ene

Optimization & Training · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Alina Ene trusts overall

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

  1. Yurii E. Nesterov
  2. H. Brendan McMahan
  3. Arkadi Nemirovski
  4. Arkadi S. Nemirovsky
  5. Diederik P. Kingma
  6. John C. Duchi
  7. Eric Balkanski
  8. Devdatt P. Dubhashi
  9. Panayotis Mertikopoulos
  10. Gauthier Gidel

Who trusts Alina Ene overall

  1. Matthew Fahrbach
  2. Eric Balkanski
  3. Jesse Vig
  4. Yaron Singer
  5. Vahab S. Mirrokni
  6. Sharon Qian
  7. Adam Breuer
  8. Morteza Zadimoghaddam
  9. Sebastian Gehrmann
  10. Antonio Orvieto

Papers from Alina Ene's perspective

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

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

Their papers