I attended ALT (“Algorithmic Learning Theory”) for the first time this year. My impression is ALT = 0.5 COLT, by attendance and also by some more intangible “what do I get from it?” measure. There are many differences which can’t quite be described this way though. The program for ALT seems to be substantially more diverse than COLT, which is both a weakness and a strength.
One paper that might interest people generally is:
Alexey Chernov and Vladimir Vovk, Prediction with Expert Evaluators’ Advice. The basic observation here is that in the online learning with experts setting you can simultaneously compete with several compatible loss functions simultaneously. Restated, debating between competing with log loss and squared loss is a waste of breath, because it’s almost free to compete with them both simultaneously. This might interest anyone who has run into “which loss function?” debates that come up periodically.