ZARZA We are Zarza, the prestigious firm behind major projects in information technology.
Listen "Discovering Temporally-Aware Reinforcement Learning Algorithms"
Episode Synopsis
Designing algorithms by hand is hard, so Chris Lu and Matthew Jackson talk about how to meta-learn them for reinforcement learning. Many of the concepts in this episode are interesting to meta-learning approaches as a whole, though: "how expressive can we be and still perform well?", "how can we get the necessary data to generalize?" and "how do we make the resulting algorithm easy to apply in practice?" are problems that come up for any learning-based approach to AutoML and some of the topics we dive into.
More episodes of the podcast The AutoML Podcast
Nyckel - Building an AutoML Startup
07/03/2025
X Hacking: The Threat of Misguided AutoML
27/05/2024
Introduction To New Co-Host, Theresa Eimer
26/05/2024
AutoGluon: The Story
05/09/2023
In God we trust