Michael Pohl

Artificial Intelligence · 2011

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Pohl trusts overall

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

  1. Thorsten Joachims
  2. Radford M. Neal
  3. Tong Zhang
  4. Martin A. Zinkevich
  5. Muthu Dayalan
  6. Shai Shalev-Shwartz

Papers from Michael Pohl's perspective

Ordered by how strongly the researchers Michael Pohl 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. Pegasos: primal estimated sub-gradient solver for SVM
  5. Pattern Recognition and Machine Learning
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. RCV1: A New Benchmark Collection for Text Categorization Research
  9. Latent Dirichlet Allocation
  10. Learning Multiple Layers of Features from Tiny Images

Their papers