The Gradient
The Gradient: Perspectives on AI
Ryan Tibshirani: Statistics, Nonparametric Regression, Conformal Prediction

Ryan Tibshirani: Statistics, Nonparametric Regression, Conformal Prediction

On scholarship in the statistics community, trend filtering, conformal prediction, and epidemic forecasting.

Episode 121

I spoke with Professor Ryan Tibshirani about:

  • Differences between the ML and statistics communities in scholarship, terminology, and other areas.

  • Trend filtering

  • Why you can’t just use garbage prediction functions when doing conformal prediction

Ryan is a Professor in the Department of Statistics at UC Berkeley. He is also a Principal Investigator in the Delphi group. From 2011-2022, he was a faculty member in Statistics and Machine Learning at Carnegie Mellon University. From 2007-2011, he did his Ph.D. in Statistics at Stanford University.

Reach me at for feedback, ideas, guest suggestions.

The Gradient Podcast on: Apple Podcasts  | Spotify | Pocket Casts | RSS
Follow The Gradient on Twitter


  • (00:00) Intro

  • (01:10) Ryan’s background and path into statistics

  • (07:00) Cultivating taste as a researcher

  • (11:00) Conversations within the statistics community

  • (18:30) Use of terms, disagreements over stability and definitions

  • (23:05) Nonparametric Regression

    • (23:55) Background on trend filtering

    • (33:48) Analysis and synthesis frameworks in problem formulation

    • (39:45) Neural networks as a specific take on synthesis

    • (40:55) Divided differences, falling factorials, and discrete splines

      • (41:55) Motivations and background

      • (48:07) Divided differences vs. derivatives, approximation and efficiency

  • (51:40) Conformal prediction

    • (52:40) Motivations

    • (1:10:20) Probabilistic guarantees in conformal prediction, choice of predictors

    • (1:14:25) Assumptions: i.i.d. and exchangeability — conformal prediction beyond exchangeability

    • (1:25:00) Next directions

  • (1:28:12) Epidemic forecasting — COVID-19 impact and trends survey

    • (1:29:10) Survey methodology

    • (1:38:20) Data defect correlation and its limitations for characterizing datasets

  • (1:46:14) Outro


The Gradient
The Gradient: Perspectives on AI
Deeply researched, technical interviews with experts thinking about AI and technology. Hosted, recorded, researched, and produced by Daniel Bashir.