EPISODE · Dec 7, 2018 · 40 MIN
Unbiased Learning from Biased User Feedback with Thorsten Joachims - TWiML Talk #207
from The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) · host Sam Charrington
In the final episode of our re:Invent series, we're joined by Thorsten Joachims, Professor in the Department of Computer Science at Cornell University. We discuss his presentation “Unbiased Learning from Biased User Feedback,” looking at some of the inherent and introduced biases in recommender systems, and the ways to avoid them. We also discuss how inference techniques can be used to make learning algorithms more robust to bias, and how these can be enabled with the correct type of logging policies.
What this episode covers
In the final episode of our re:Invent series, we're joined by Thorsten Joachims, Professor in the Department of Computer Science at Cornell University. We discuss his presentation “Unbiased Learning from Biased User Feedback,” looking at some of the inherent and introduced biases in recommender systems, and the ways to avoid them. We also discuss how inference techniques can be used to make learning algorithms more robust to bias, and how these can be enabled with the correct type of logging policies.
NOW PLAYING
Unbiased Learning from Biased User Feedback with Thorsten Joachims - TWiML Talk #207
No transcript for this episode yet
Similar Episodes
Mar 26, 2026 ·1m
Mar 19, 2026 ·34m
Feb 18, 2026 ·11m
Feb 11, 2026 ·45m