Laura Niss

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Laura Niss trusts overall

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

  1. Moritz Hardt
  2. Richard S. Zemel
  3. Michael Feldman

Papers from Laura Niss's perspective

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

  1. Fairness through awareness
  2. Equality of Opportunity in Supervised Learning
  3. Certifying and Removing Disparate Impact
  4. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
  5. Learning Fair Representations
  6. Fairness in Learning: Classic and Contextual Bandits
  7. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
  8. ImageNet classification with deep convolutional neural networks
  9. Learning Multiple Layers of Features from Tiny Images
  10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers