On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems — mentioned by noelwelsh

Wed, 30 May 2012 12:54:37 GMT

So Ben, looks like it's time to cross swords again :) 1. Real world performance varies over time... I don't really understand this complaint. With A/B testing, you have to collect enough data before making a decision that the conversion rate fluctuations average out. If you're worried about monthly fluctuations (which is reasonable), and you're doing A/B testing, you need to collect data for a few months. This means months where you aren't optimising. With a bandit algorithm conversion rate fluctuations will cause changes in the bandit behaviour, but they will average out over time just like…

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On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems · HackerPapers discussions

On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems — mentioned by noelwelsh