Welcome to our July 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we report on IJCAI-ECAI, ICML and RoboCup, listen to the first episode of the GRACE podcast, and find out who won the AI Song Contest. Back as an in-person event for the first time since 2019, Bangkok played host to RoboCup2022, where around 1500 participants, from 39 different countries took part in competitions and a symposium. You can see the programme of events here, and there are links to the recordings of the competitions for some of the leagues here. If you are interested in reading our interviews from last year with members of the different leagues, these can be found here.

The International Conference on Machine Learning (ICML) Test of Time award is given to a paper from ICML ten years ago that has had significant impact. The paper investigates adversarial machine learning and, specifically, poisoning attacks on support vector machines (SVMs). The awards committee noted that this paper is one of the earliest and most impactful papers on the theme of poisoning attacks, which are now widely studied by the community. The authors use a gradient ascent strategy in which the gradient is computed based on properties of the SVM's optimal solution. The method can be kernelized, thereby not needing explicit feature representation.

The International Conference on Machine Learning (ICML) Test of Time award is given to a paper from ICML ten years ago that has had significant impact. This year the award goes to Niranjan Srinivas, Andreas Krause, Sham Kakade and Matthias Seeger for their work "Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design". This paper brought together the fields of Bayesian optimization, bandits and experimental design by analyzing Gaussian process bandit optimization, giving a novel approach to derive finite-sample regret bounds in terms of a mutual information gain quantity. This paper has had profound impact over the past ten years, including the method itself, the proof techniques used, and the practical results. These have all enriched our community by sparking creativity in myriad subsequent works, ranging from theory to practice.

Organizers of the 37th International Conference on Machine Learning (ICML) have announced this year's Test of Time award, which goes to a team from the California Institute of Technology, University of Pennsylvania, Saarland University. The ICML Test of Time award recognizes an ICML paper from ten years ago that has proven influential, with significant impacts in the field, "including both research and practice." Authors: Niranjan Srinivas, Andreas Krause, Sham Kakade, Matthias Seeger Institutions: California Institute of Technology, University of Pennsylvania, Saarland University Abstract: Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low RKHS norm. We resolve the important open problem of deriving regret bounds for this setting, which imply novel convergence rates for GP optimization.

At NeurIPS this week in Vancouver, Canada more than 1,400 pieces of AI research are being examined for their novel approaches or breakthroughs -- but one of these papers is unlike all the rest. Microsoft Research's Lin Xiao was named winner of the Test of Time award this week, a title granted to AI research that's made important and lasting contributions to the AI field over the last 10 years. A specially made committee is convened to look back at papers published at NeurIPS 10 years ago and narrows the list down to 18 papers that have had a lasting influence on machine learning, measured in part by which papers garnered the most citations in the past decade. To date, Xiao's paper has been cited more than 600 times by other researchers. NeurIPS organizers announced Xiao's work as the winner Sunday, and he detailed the results and progress made since then in a conference hall with 1,000 of the conference's 13,000 attendees.