3 ms·
Sure. I was merely giving an entry-level example of a "principled" approach that would handle this situation. So the concern then is the time it takes to conve
by tansey 15y ago
Sure. I was merely giving an entry-level example of a "principled" approach that would handle this situation.
So the concern then is the time it takes to converge on an optimal value? Is that even possible?
I'm not a content optimization expert by any means, so I'm just curious if we have any evidence that the landscape is static. It seems entirely possible (maybe even probable) that an optimal option now may grow stale and actually be suboptimal next week/month.
- noelwelsh 15y agoYou're basically correct in your assessment. The time to converge to the optimal action is formalised as the accumulated regret. This is the sum of the error made over time. If you assume the landscape is static -- called stationary in the literature -- you can achieve within a constant factor of optimal regret. Good algorithms only differ in their constant factors. If the landscape is not static it is called non-stationary. Amazingly you can still be optimal (for a slightly different definition of optimal) in the non-stationary case! This is called the nonstochastic bandit in the literature. Finally, are websites static or not? It depends :) However it seems that most are static. At least the one where we're applying our tech. are. Something like Amazon probably wouldn't be, but the non-stationary bits of their problem are probably best viewed as a product recommendation problem. UI tweaks might still be reasonably modelled as stationary.