Conference on Learning Theory COLT 2022 by Antonin Schrab

« COLT has been the prime annual meeting of the growing learning theory community for 35 years now, and that London edition has been beyond our expectations. We have been planning COLT 2022 since late 2019, and due to Covid it was unclear until a few weeks before the conference how many people would be able or willing to join. Our optimistic scenario was 150 on site attendees — we ended up at more than 270! COLT 2022 featured the higher number ever of papers (155) in a dual track format. I am especially proud that over 50% of attendees were MSc, PhD and postdocs: COLT has long been a welcoming and inclusive forum for early-career researchers. As local chair, COLT has eaten up a lot of my days and nights recently, but it certainly was worth it! » Benjamin Guedj, Inria and University College London, COLT 2022 Local Chair.

This July, I’ve had the great pleasure of participating in the Conference on Learning Theory COLT 2022 which has been held in person in London! I found the conference to be a real success, it was wonderful to finally be able to meet so many people sharing the same interests in learning theory! It was amazing to follow talks held in the historic Royal Institution of Great Britain which is the location of the famous televised Christmas Lectures!

The conference kicked off with a joint workshop between COLT and IMS (Institute of Mathematical Statistics) Annual Meeting with tutorials and talks by Emmanuel Candès, Nati Srebro and Vladimir Vovk on the topics of conformal prediction and mathematics of deep learning. This workshop allowed to bring together both audience (IMS and COLT) with aligned interests on statistics and learning theory. This was a great initiative which was really appreciated by all the participants I talked to, I hope the joint workshop between IMS and COLT will remain in future editions of the conferences!

During the four following days, all papers accepted to COLT 2022 have been presented by the authors. Each talk was ten minutes long, this format allowed to get a good overview of each of the 155 papers. Topics included Online Learning, Statistics, Privacy, Robustness, Computational Complexity, Deep Learning, Generalization, Bandits, Sampling, Optimization, Graphs, Information Theory, Reinforcement Learning and Control. It was also very interesting to listen to longer talks such as those of the two papers which received the best paper and best student paper awards of COLT 2022 (Efficient Convex Optimization Requires Superlinear Memory by Annie Marsden, Vatsal Sharan, Aaron Sidford, and Gregory Valiant, and New Projection-Free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees by Ben Kretzu and Dan Garber), as well as those given by plenary speakers: Jelani Nelson from Berkeley, University of California, Maryam Fazel from University of Washington, and Alon Orlitsky from University of California San Diego.

I also really enjoyed the open problem sessions in which unsolved problems were presented in the hope that these can be solved in future editions of COLT, it was great to see which learning theory problems people currently find challenging! Other events were also organised such as the LeT-All career panel providing advice to early researchers, the Women in Machine Learning Theory luncheon discussing everyday challenges women are facing in academic and industrial Machine Learning research, the business meeting with COLT announcements about future editions of the conference, the workshop reception and the conference gala dinner which were the perfect opportunity to engage with other participants!

COLT 2022 was made possible thanks to the hard-working organizing committee: program chair Po-Ling Loh from University of Cambridge, program chair Maxim Raginsky from University of Illinois at Urbana-Champaign, local chair Benjamin Guedj from Inria and University College London, local chair Ciara Pike-Burke from Imperial College London, open problems chair Clément Canonne from University of Sydney, online experience chair Claire Vernade from DeepMind, and publication chair Suriya Gunasekar from Microsoft Research. Thank you all for making COLT 2022 possible and such a success!

I am now looking forward to COLT 2023!