John Moeller

Artificial Intelligence · 2014

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

Whom John Moeller trusts overall

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

  1. Toon Calders
  2. Faisal Kamiran

Who trusts John Moeller overall

  1. Muhammad Bilal Zafar
  2. Indrė Žliobaitė
  3. Lu Zhang
  4. Silvia Chiappa
  5. Kush R. Varshney
  6. Isabel Valera
  7. Sorelle A. Friedler
  8. Shira Mitchell
  9. Xintao Wu
  10. Patrick Hall

Papers from John Moeller's perspective

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

  1. Fairness-aware Learning through Regularization Approach
  2. Fairness through awareness
  3. Classifying without discriminating
  4. Integrating induction and deduction for finding evidence of discrimination
  5. A multidisciplinary survey on discrimination analysis
  6. Big Data's Disparate Impact
  7. k-NN as an implementation of situation testing for discrimination discovery and prevention
  8. Building Classifiers with Independency Constraints
  9. Learning Fair Representations
  10. LIBLINEAR: A Library for Large Linear Classification

Their papers