Before revision: We propose a cumulative oversampling (CO) technique for Thompson Sampling (TS)to construct optimistic parameter estimates with significantly fewer samples than existing oversampling frameworks .
After revision: We propose a cumulative oversampling (CO) method for online learning. Our key idea is to sample parameter estimations from the updated belief space once in each round (similar to Thompson Sampling), and utilize the cumulative samples up to the current round to construct optimistic parameter estimates with significantly fewer samples than existing oversampling frameworks .