Paul R. Dixon

2010

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Paul R. Dixon trusts overall

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

  1. Hanna M. Wallach
  2. Haizhou Li

Papers from Paul R. Dixon's perspective

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

  1. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
  2. Efficient Training of Conditional Random Fields
  3. A Joint Source-Channel Model for Machine Transliteration
  4. A tutorial on hidden Markov models and selected applications in speech recognition
  5. Inducing Features of Random Fields
  6. Interpolated estimation of Markov source parameters from sparse data
  7. Scikit-learn: Machine Learning in Python
  8. GradientBased Learning Applied to Document Recognition
  9. Enriching Word Vectors with Subword Information
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers