University of Birmingham > Talks@bham > Theoretical computer science seminar > Categorical Semantics of Learning by Gradient Descent

Categorical Semantics of Learning by Gradient Descent

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact George Kaye.

Zoom details


I will present recent and ongoing work on giving a semantic foundation to training algorithms in machine learning using the categorical formalisms of lenses. Lenses provide a unifying perspective on various classes of such algorithms, as well as offering a different style of specifying and proving properties of training protocols. They also enable the study of machine learning for new classes of models such as Boolean circuits and polynomial circuits. In the last part of the talk I will discuss some applications and directions for future work, including circuit design for hardware implementation, formal verification of learning algorithms, and accounting for learning beyond stochastic gradient descent.

This talk is part of the Theoretical computer science seminar series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


Talks@bham, University of Birmingham. Contact Us | Help and Documentation | Privacy and Publicity.
talks@bham is based on from the University of Cambridge.