To join this seminar, please register via Zoom. Once your registration is approved, you'll receive an email with details on how to join the meeting.
If you have any questions about your registration or the seminar, please contact headsec [at] stat.ubc.ca.
The four pillars of machine learning
I will present a unified perspective on the field of machine learning research, following the structure of my recent book, "Probabilistic Machine Learning: Advanced Topics" (https://probml.github.io/book2). In particular, I will discuss various models and algorithms for tackling the following four key tasks, which I call the "pillars of ML": prediction, control, discovery and generation. For each of these tasks, I will also briefly summarize a few of my own contributions, including methods for robust prediction under distribution shift, statistically efficient online decision making, discovering hidden regimes in high-dimensional time series data, and for generating high-resolution images.
van Eeden speakers
Dr. Kevin Patrick Murphy has been invited by our department's graduate students to be this year's van Eeden speaker. A van Eeden speaker is a prominent statistician who is chosen by our graduate students each year to give a lecture, supported by the Constance van Eeden Fund.
This seminar is sponsored by Canadian Statistical Sciences Institute (CANSSI).