[gov3009-l] Applied Stats - 4/29 - Finale Doshi-Velez

Anton Strezhnev astrezhnev at fas.harvard.edu
Mon Apr 27 11:04:29 EDT 2015

Hi everyone!

This week at the Applied Statistics Workshop we will be welcoming *Finale
Doshi-Velez,* a Professor of Computer Science at the Harvard School of
Engineering and Applied Sciences. She will be presenting work entitled
Or-of-And Models for Interpretable Classification*.  Please find the
abstract below and on the website

As usual, we will meet in CGIS Knafel Room 354 and lunch will be provided.
See you all there!

-- Anton

Title: Bayesian Or-of-And Models for Interpretable Classification

Abstract: Interpretability is an important factor for models to be used and
trusted in many applications.  Disjunctive normal forms, also known as
or-of-and models, are models with classification rules of the form "Predict
True if (A and B) or (A and C) or D."  They are an appealing form of
classifier because one can easily trace how a classification decision was
made, and has some basis in human decision-making.  In this talk, I will
talk about a Bayesian approach to learning or-of-and models and describe an
application to context-aware recommender systems.

This is joint work with Tong Wang and Cynthia Rudin
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