Convergence of Online SGD under Infinite Noise Variance, and Non-convexity

A lecture exploring alternatives to using labeled training data. Labeled training data is often scarce, unavailable, or can be very costly to obtain. To circumvent this problem, there is a growing in...

A high-level overview of key areas of AI ethics and not-ethics, exploring the challenges of algorithmic decision-making, kinds of bias, and interpretability, linking these issues to problems of human-...

A brief introduction to various legal and procedural ethical concepts and their applications within and beyond academia. It's all very well to talk about truth, beauty and justice for academic researc...

David Steinsaltz gives a lecture on the ethical issues in statistics using historical examples. ...

This seminar explains and illustrates the approach of Markov melding for joint analysis. Integrating multiple sources of data into a joint analysis provides more precise estimates and reduces the risk...

Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping. Using an extended and formalized version of the Q/C map analysis of Pool et al. (2016...

Andy Gittings and Dai Jenkins, deliver a graduate lecture on Advance Research Computing (ARC)....

Professor Denise Lievesley discusses ethical issues and codes of conduct relevant to applied statisticians. Statisticians work in a wide variety of different political and cultural environments which...

Maria Christodoulou and Mariagrazia Zottoli share what a standard day is like for a statistics consultant. ...