Category: Technical Methodology (Math-Heavy)
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My Math Review Notes
I recently took the first-year screening exam for Ph.D. students in the statistics group in the Department of Data Sciences and Operations at Marshall. Since I started applying to grad school, I’ve been writing up review notes to help me with math. Originally the purpose of the notes was to help me study for the…
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Our Entry in the OCRUG Hackathon 2019
I was a part of Team Save the WoRld along with Faizan Haque, Javier Orraca, Sam Park, and Shruhi Desai in the OCRUG Hackathon 2019 held at UC Irvine on May 18th and 19th. (In fact, I am writing this blog post at the tail end of our time before we present our results!) The…
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Presentation on Multi-Task Learning
Today I gave an in-class presentation at USC on two papers in multi-task learning (or multivariate regression–linear regression when the response is a vector rather than one number). You could simply train a separate model for each response, but when the responses are related, there are advantages to considering them all at the same time…
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The McCarthy/Fader/Hardie Model for Customer Retention
In another post, I described how I fit a model to predict how well Buffer—a digital subscription-based firm that publicly releases much of its financial data—retains its customers. I used a methodology developed by Daniel McCarthy, Peter Fader, and Bruce Hardie (paper available for free download here) to fit the model. In this post, I’ll fill in…