ml theory series

The ML Theory series, co-organised with Databased, consists of a set of mini-courses covering topics in Theoretical Machine Learning. Each mini-course is complemented by invited talks from faculty members and researchers at industrial research labs, highlighting state-of-the-art developments in the respective areas.

Reinforcement Learning

Date Lecture Topic Instructor Notes
6 Jan 2026 Markov Decision Processes, Value Iteration Kintan Saha Slides  |  Scribe  |  Recording
8 Jan 2026 Policy Iteration, Temporal Difference Learning Kintan Saha Slides  |  Scribe  |  Recording
10 Jan 2026 Stochastic Approximation, Convergence of TD Kintan Saha Slides  |  Scribe  |  Recording
12 Jan 2026 Q Learning, Policy Gradient Methods Kintan Saha, Ishaq Hamza Slides  |  Scribe  |  Recording
14 Jan 2026 Actor-Critic Methods Ishaq Hamza Slides  |  Scribe  |  Recording
20 Jan 2026 Multi-Agent Systems - I Siddharth Reddy Slides  |  Scribe  |  Recording
22 Jan 2026 Multi-Agent Systems - II Siddharth Reddy Slides  |  Scribe  |  Recording

Overparametrized Models

Date Lecture Topic Instructor Notes
27 Jan 2026 Sahil Chaudhary Slides  |  Scribe  |  Recording
29 Jan 2026 Sahil Chaudhary Slides  |  Scribe  |  Recording
03 Feb 2026 Sahil Chaudhary Slides  |  Scribe  |  Recording
05 Feb 2026 Sahil Chaudhary Slides  |  Scribe  |  Recording

Diffusion Models

Date Lecture Topic Instructor Notes
24 Feb 2026 Nishanth Shetty Slides  |  Scribe  |  Recording
26 Feb 2026 Nishanth Shetty Slides  |  Scribe  |  Recording
03 Mar 2026 Nishanth Shetty Slides  |  Scribe  |  Recording
05 Mar 2026 Nishanth Shetty Slides  |  Scribe  |  Recording