Beongjun Choi

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Beongjun Choi trusts overall

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

  1. Jeremy Bernstein
  2. Min Ye

Papers from Beongjun Choi's perspective

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

  1. Large Scale Distributed Deep Networks
  2. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
  3. TensorFlow: A system for large-scale machine learning
  4. Automatic differentiation in PyTorch
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Scaling Distributed Machine Learning with the Parameter Server
  7. TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
  8. Gradient-based learning applied to document recognition
  9. Communication-Efficient Learning of Deep Networks from Decentralized Data
  10. Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent

Their papers