Pascal Bianchi

Optimization & Training · 2011–2019

A researcher in the Science corpus: 5 papers; trusts 89 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

Whom Pascal Bianchi trusts overall

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

  1. Angelia Nedić
  2. John N. Tsitsiklis
  3. Yurii E. Nesterov
  4. Shai Shalev-Shwartz
  5. Dimitri P. Bertsekas
  6. Robert Tibshirani
  7. Vivek Shripad Borkar
  8. Morris H. Degroot
  9. Patrick L. Combettes
  10. Michael G. Rabbat

Who trusts Pascal Bianchi overall

  1. P. Lorenzo
  2. Ali H. Sayed
  3. Jinshan Zeng
  4. Shi Pu
  5. Simone Scardapane
  6. Yan Zhang
  7. Alexander Olshevsky
  8. Franck Iutzeler
  9. Donghwan Lee
  10. Antoine Godichon-Baggioni

Papers from Pascal Bianchi's perspective

Ordered by how strongly the researchers Pascal Bianchi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers