James Thomas

Artificial Intelligence · with Kuiper · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom James Thomas trusts overall

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

  1. Leo Breiman
  2. Andrew Y. Ng
  3. Thomas G. Dietterich

Papers from James Thomas's perspective

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

  1. Dropout: a simple way to prevent neural networks from overfitting
  2. GloVe: Global Vectors for Word Representation
  3. Bagging Predictors
  4. Text Categorization with Support Vector Machines: Learning with Many Relevant Features
  5. Term-Weighting Approaches in Automatic Text Retrieval
  6. ImageNet classification with deep convolutional neural networks
  7. Multiple Classifier Systems
  8. Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures
  9. A comparison of event models for naive bayes text classification
  10. Feature selection, L1 vs. L2 regularization, and rotational invariance

Their papers