# Neurips Image

I am creating this post because Neurips 2020 wants us to upload an image of our paper. The best image we could come up is the one of the regret bound of our algorithm :D

Oh, I 'member!

I am creating this post because Neurips 2020 wants us to upload an image of our paper. The best image we could come up is the one of the regret bound of our algorithm :D

Given a real symmetric matrix $H \in \mathbb{R}^{n\times n}$, we can show that:

If not, check this!

I think so, but how to efficiently display it?

You should, because of this. Actually, that was the Woodbury formula. As a special case, we have the Sherman-Morrison update, which we here implement in Python:

Multi-armed bandit algorithms are becoming more and more important in the field of machine learning (at least to me, since I started a PhD on this topic :D). This funny name derives from the one-armed bandit, a name used for a lever operated slot machine (and apparently also for a Belgian rock album).

Variance? Whaaaat?