AIT&ML Community Hub (live now) -and- Online&InPerson Symposium soon (30-31 July)

[Marcus Hutter]

For those interested in the intersection of Algorithmic Information Theory (AIT) and Machine Learning (ML):

We have just launched a community site for UAI/ASI enthusiasts.
Universal Algorithmic Intelligence (UAI): Community hub for researchers interested in Solomonoff Induction, AIXI, etc.
https://uaiasi.wordpress.com/
(if you experience problems with the subscribe button, please email <cole...@gmail.com>

The "Symposium on Algorithmic Information Theory and Machine Learning" starts in 2 days,
30 -31 July 2025, Imperial College London, London, UK
https://sites.google.com/corp/site/boumedienehamzi/second-symposium-on-algorithmic-information-theory-and-machine-learning
which you are all welcome to attend (online or in person) - it's free!

Kind regards,

Marcus
______________________
Marcus Hutter,
Australian National University (Honorary Professor)
Google DeepMind, London (Senior Researcher)
http://www.hutter1.net/

Second Symposium on Algorithmic Information Theory and Machine Learning,
30 -31 July 2025, Imperial College London, London, UK.

Following the success of the 1st edition held at the Alan Turing Institute, London, UK, on 4–5 July 2022 (see details), this symposium continues to explore the rich interface between Algorithmic Information Theory (AIT) and Machine Learning (ML).

Objective:
The symposium aims to bring together researchers working at the intersection of AIT and ML, with a particular focus on the application of concepts such as Kolmogorov Complexity and algorithmic probability to contemporary ML problems. Topics of interest include, but are not limited to:

Using AIT to explain a priori why certain ML methods succeed (or fail) on specific problems
Theoretical foundations and practical applications of Solomonoff induction
Connections between information theory, learning, and data compression
Developing ML algorithms for improved prediction and compression that approximate Kolmogorov Complexity
Probabilistic modeling through algorithmic probability frameworks
Kernel methods for AIT, and vice versa.

Organizing Committee: Boumediene Hamzi, Kamaludin Dingle, Marcus Hutter

Join Us at: https://sites.google.com/corp/site/boumedienehamzi/second-symposium-on-algorithmic-information-theory-and-machine-learning
Whether you plan to attend in person or online, or simply wish to stay informed about future events and updates on AIT & ML, please complete the interest form here.