Overview
Pedro Domingos is a computer scientist (Professor Emeritus, University of Washington), a prominent machine-learning researcher known for work on classification, Markov logic networks, and for the popular-science book The Master Algorithm.
Key Contributions / Features
- Optimality of naive Bayes (Domingos-Pazzani 1997): with Michael Pazzani, explained why the naive Bayes classifier is often optimal under zero-one loss despite violating its independence assumption (Naive Bayes Classifier).
- Work on Markov logic networks (unifying logic and probability), rule/tree learning, and the theory of machine learning.
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