Dear researchers,
Centrum Wiskunde & Informatica (CWI) kindly invites you to the
eight Seminar++ meeting on Machine Learning Theory, taking place
on Wednesday June 21 from 15:00 - 17:00. These Seminar++ meetings
consist of a one-hour lecture building up to an open problem,
followed by an hour of brainstorming time. The meeting is intended
for interested researchers including PhD students. These meetings
are freely accessible without registration. Cookies, coffee and
tea will be provided in the half-time break.
The meeting of 21 June will be hosted by:
Alexander Ly, Postdoc at the Centrum Wiskunde & Informatica.
Abstract: The safe anytime-valid inference framework based on e-values allows practitioners to adaptively design their experiments and draw more reliable conclusions compared to conventional p-value-based approaches. The presentation begins with a concise overview of the recently developed general theory of e-values and the various procedures to construct them. In order to distinguish among the different e-values, Grünwald, de Heide and Koolen (2019) introduced the GROW criterion along with a general procedure specifically designed to construct the optimal e-value according to this criterion. Practical considerations and the context of the statistical problem itself might lead us to deviate from recommending this so-called GROW e-value. We shed light on the choices we made when constructing e-values for fundamental classical inference problems, such as z-tests, t-tests, one-way ANOVAs, and (generalised) linear models. Our objective is to investigate the potential generalisability of these context-specific solutions to a broader range of inference problems in hope to expand the practicality and versatility of safe anytime-valid inference.
The event takes place in room L016 in the CWI building, Science
Park 123, Amsterdam.
The Seminar++ Meetings are part of the Machine
Learning Theory Semester Programme, which runs in Spring
2023.
Best regards on behalf of CWI from the program committee,
Wouter Koolen