Recent years have witnessed an increased cross-fertilisation between the fields of statistics and computer science. In the era of Big Data, statisticians are increasingly facing the question of guaranteeing prescribed levels of inferential accuracy within certain time budget. On the other hand, computer scientists are progressively modelling data as noisy measurements coming from an underlying population, exploiting the statistical regularities of the data to save on computation.
This cross-fertilisation has led to the development and understanding of many of the algorithmic paradigms that underpin modern machine learning, including gradient descent methods and generalisation guarantees, implicit regularisation strategies, high-dimensional statistical models and algorithms.
About the event
This event will bring together experts to talk about advances at the intersection of statistics and computer science in machine learning. This two-day conference will focus on the underlying theory and the links with applications, and will feature 12 talks by leading international researchers.
The intended audience is faculty, postdoctoral researchers and Ph.D. students from the UK/EU, in order to introduce them to this area of research and to the Turing.
Monday 13 (10:00 - 18:30) and Tuesday 14 January (10:00 - 17:30)
Both days will include 6 talks and day 1 will finish with a poster session and networking reception.
- Carola-Bibiane Schonlieb (University of Cambridge)
- Caroline Uhler (Massachusetts Institute of Technology)
- Francis Bach (Centre de Recherche INRIA de Paris)
- Garvesh Raskutti (University of Wisconsin-Madison)
- Jean-Philippe Vert (Google)
- Florent Krzakala (Sorbonne Université)
- Lorenzo Rosasco (University of Genova)
- Madeleine Udell (Cornell University)
- Peter Bartlett (UC Berkeley)
- Rebecca Willett (University of Chicago)
- Tamara Broderick (Massachusetts Institute of Technology)
- Vitaly Feldman (Google Brain)
This workshop is sponsored by The Alan Turing Institute and Google
Presenting a poster
Students wishing to present a poster at the event should send an email to Varun Kanade ([email protected]) including the title, abstract, list of authors and whether their work on that topic has already been published (or accepted) at a conference or journal.
If we get more requests than feasible for presentation at the venue, the organisers will apply a light review process.
This event has now sold out.
Funding available to support travel
Updated on 21 November 2019.
Limited funds are available to support students to travel to the conference. We particularly welcome participation from under-represented minorities in Machine Learning. Students wishing to avail of support should send a short email explaining their case, CV, and contact details of their supervisor to Varun Kanade ([email protected]) by Friday 6 December 2019.
The decision of support will be confirmed and awarded after the event. If you have submitted a request and cannot attend the event without the support, please inform Varun Kanade.
Travel funds are supported by The Alan Turing Institute and Google.
The Alan Turing Institute will offer a refund, minus service and administration fees, until Monday 16 December 2019 (4 weeks prior to the event).