Workshop on Stein's Method in Machine Learning and Statistics beach

International Conference on Machine Learning 2019

Date: Fri. 14th or Sat. 15th June 2019.

Location: Long Beach Convention Center.


Stein's method is a technique from probability theory for bounding the distance between probability measures using differential and difference operators. Although the method was initially designed as a technique for proving central limit theorems, it has recently caught the attention of the machine learning (ML) community and has been used for a variety of practical tasks. Recent applications include goodness-of-fit testing, generative modeling, global non-convex optimisation, variational inference, de novo sampling, constructing powerful control variates for Monte Carlo variance reduction, and measuring the quality of Markov chain Monte Carlo algorithms.

Although Stein's method has already had significant impact in ML, most of the applications only scratch the surface of this rich area of research in probability theory. Significant gains could be made by encouraging both communities to interact directly, and this workshop aims to facilitate this discussion.

The workshop will begin with an introduction to Stein's method which will be accessible for researchers in machine learning who are unfamiliar with the topic. It will then consist of an alternating sequence of invited talks from machine learning researchers and experts in Stein's method, which will highlight both foundational topics and applications in machine learning and statistics. The workshop will also include a session for contributed posters and will conclude with a panel discussion to elicit a concise summary of the state of the field.

Call for Contributed Posters

The workshop is looking for contributed posters on all aspects of Stein's method, including foundational work and/or its application to any topic relating to machine learning or statistics. Submissions can either be about novel work, or be based on recently published papers. We particularly welcome submissions which aim to spark discussions on novel uses of Stein's method in machine learning, statistics and related topics.

To contribute to the workshop, please send a half-page abstract in pdf form to steinworkshop [at] The submissions will then be reviewed by a panel consisting of the organisers of the workshop, and be accepted based on their relevance to the workshop as highlighted above.

This workshop aims to be inclusive, and we therefore particularly encourage submissions from under-represented communities.

Note that four complimentary workshop registrations are available. Please indicate whether you would like to be considered for these when submitting your proposal. Complimentary registrations will be prioritised for early-career researchers.

Deadline for submissions: 10th May 2019

Accepted posters announced: 17th May 2019


Registration for this workshop is through the main ICML website. We encourage participants to register as soon as possible as places are limited and often fill up quickly.

Invited Speakers