Michael Ridley

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Ridley trusts overall

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

  1. Kevin Bauer
  2. Perry Sadorsky
  3. Leo Guelman

Who trusts Michael Ridley overall

  1. Alejandro Barredo Arrieta
  2. Atoosa Kasirzadeh
  3. Vaishak Belle
  4. Natalia Díaz Rodríguez
  5. Qinbin Li
  6. Davinder Kaur
  7. Liat Antwarg
  8. Eduardo Mosqueira-Rey
  9. Upol Ehsan
  10. Khansa Rasheed

Papers from Michael Ridley's perspective

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

  1. A Unified Approach to Interpreting Model Predictions
  2. Towards A Rigorous Science of Interpretable Machine Learning
  3. Scikit-learn: Machine Learning in Python
  4. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
  5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  6. XGBoost: A Scalable Tree Boosting System
  7. Consistent Individualized Feature Attribution for Tree Ensembles
  8. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead
  9. Greedy function approximation: A gradient boosting machine.
  10. Stochastic gradient boosting

Their papers