The only methods to get these bounds I knew are the iterative rounding and the discrepancy techniques. Now I am curious to look into this herding procedure.

]]>Thank you for share. ]]>

the bandit monograph contains most of what you should know to start doing research on bandit-related problems. The two other set of lecture notes are useful to place bandit problems within the broader context of optimization and online learning. Obviously there are many other useful references besides these ones, but it’s probably a good idea to first try to master the bandit monograph.

]]>I’m a PhD student in statistics and beginner for Bandit-related problems.

I was wondering that in order to get involved in this fruitful field, besides your basic bandit monograph, should I also go through your two published optimization lecture notes (intro.to online optimization & theory of convex optimization) ? Any suggestions to beginners?

Thanks a lot!

Best,

Eric