Welcome to my homepage. I am an associate professor at the Korteweg-de Vries Institute for Mathematics at the University of Amsterdam in the Netherlands. My research is about the mathematical foundations of machine learning.

## Research Interests in Mathematical Machine Learning

- The mathematics of explainable machine learning
- Adaptive methods in online convex optimization and prediction with expert advice
- Faster-than-minimax rates for ‘easy data’ in statistical and online learning
- PAC-Bayesian concentration inequalities
- Statistical learning theory, frequentist analysis of Bayesian methods

See also my publications.

## News

- July 2023: Elected to join the board of directors for COLT
- April 2023: I joined the board of the national AI & Mathematics initiative (AIM)
- Upcoming events:
- May 2-4, 2024: Going to AIStats in Valencia. Hope to see many people there! Hidde, Damien and I will be presenting our paper that identifies mayor fundamental problems with the approach of algorithmic recourse.
- April 19, 2024: Talk in the FOAM seminar about the query complexity of learning Nash equilibria

- Recent talks and events:
- November 17, 2023: Talk about our risks of recourse paper at the University of Amsterdam, SIAS @ LAB42
- October 27, 2023: I was in Saarbrücken for a workshop on interpretable machine learning
- November 14, 2023: Talk about our risks of recourse paper in the Columbia University statistics seminar. [slides]
- November 9, 2023: With AIM we organized a PhD networking event, with keynote by Onno Zoeter from Booking.com
- October 12, 2023: Gave a masterclass about the mathematics of explainable machine learning as part of the 3rd annual meeting for the Dutch inverse problems community in Groningen. Here are the slides.
- September 14-16, 2023: Attended EWRL 2023 in Brussels
- 12-15 July, 2023: talk at COLT 2023 about generalization guarantees via algorithm-dependent Rademacher complexity
- 19 June, 2023: talked about robust online convex optimization in the presence of outliers in the DeLTA Lab seminar at the University of Copenhagen.
- June 1-2, 2023: I was part of the organizing team for the Second workshop on AI & Mathematics (AIM) organized by the Dutch Mathematics Clusters. We put together a really cool program with great national speakers.
- I kicked off the
*Online learning in complex environments*part of the workshop on Game theory for AI organized by the University of Maastricht together with the AI and Mathematics (AIM) initiative, on March 30-31, 2023. Here are the slides. - Tutorial about Formal Results in Explainable Machine Learning as part of the CWI Machine Learning Theory Boot Camp on February 14-15, 2023. Here are the slides.

### Older News

- We have a series of great international speakers in the Statistics and Machine Learning Thematic Seminar
- I have started blogging again.
- Gave a mini-course with three lectures on adaptive online learning at the ENSAI in Rennes, 17-21 feb, 2020
- Received a VIDI grant from the Dutch Research Council
- We had the Young European Statisticians workshop on the Theoretical Foundations of Deep Learning
- Started a mailing list for machine learning in the Netherlands

## Selected Talks

- Talks about our impossibility result in explainable
machine learning. Slides are here:
- December 16, 2022, at the University of Amsterdam, SIAS @ LAB42
- November 23, 2022, at the University of Tübingen, Germany
- October 5, 2022, at the Symposium on Transparent Machine Learning organised by the Vereniging voor Statistiek en Operations Research (VVSOR).
- October 3, 2022, in the Probability & Statistics seminar at the TU Delft.

- Introduction to (distributed) online learning at the Young European Queueing Theorists workshop, Nov 2 - Nov 4, 2022. Slides are here.
- High-level talk about the relation between Statistics and Machine Learning in the Netherlands at the 1st AI & Mathematics workshop at CWI, June 9-10, 2022.
- Opening talk giving an introduction to online learning at the CWI-INRIA 2019 workshop
- Invited talk with some highlights in online convex optimization in the machine learning session at the Netherlands Mathematical Congress, 2018
- Invited talks in Toulouse, Delft, Rennes, Leuven, Poznań and Amsterdam, 2017-2018, about using multiple learning rates in online learning with MetaGrad to automatically adapt to the best possible learning rate. A related tutorial introduction to adaptive online learning at ABN AMRO, Amsterdam, 2018.
- Invited talk at Inria Lille, 2017, about fast rates in statistical and online learning. Also gave this talk in the Thematic Seminar 2018.
- Talked about MetaGrad, a new adaptive online optimization method, at the Theoretical Foundations for Learning from Easy Data workshop in Leiden, 2016
- Invited talk in the WIC Midwintermeeting 2016 on Big Data and Data Analytics
- Presented my work with Wouter Koolen on automatically learning the learning rate parameter in online learning at Benelearn 2015 and for the Leiden Centre of Data Science
- Introduction to Online Learning for a general mathematical audience in the Leiden Mathematics Colloquium, 2014
- Presented an open problem in the Online Algorithms and Learning international workshop in Leiden, 2014
- Talk about Follow the Leader with Dropout Perturbations at COLT 2014 in Barcelona
- Invited talk on convergence of the MDL estimator in the session on Model Selection in Statistical Learning at the ERCIM conference in Londen, December 14, 2013
- Invited talk about Follow the Leader If You Can, Hedge If You Must in the Learning Faster from Easy Data workshop at NIPS in Lake Tahoe, USA, December 10, 2013
- Making Regional Forecasts Add Up at the WIPFOR workshop in Paris, June 6, 2013
- The Catch-up Phenomenon in Bayesian and MDL Model Selection in the “Bayes in Paris” seminar, May 23, 2013
- Invited lecture giving An Introduction to Online Learning for Bayesians at the University of Amsterdam, February 15, 2013
- Mixability in Statistical Learning in the SMILE seminar in Paris, September 24, 2012

## Contact Information

Dr. Tim van Erven

Korteweg-de Vries Institute for Mathematics

University of Amsterdam

P.O. Box 94248

1090 GE Amsterdam

The Netherlands

Visiting address:

Science Park 107, 3rd floor (entrance via Nikhef)

Office: F3.32