most citedOnline convex optimization in the bandit setting: gradient descent without a gradient

12 citations · 12 across the 1 of their papers we have counts for

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1 paper

cs.LG2004★ 12 cited

Online convex optimization in the bandit setting: gradient descent without a gradient

Abraham D. Flaxman, Adam Tauman Kalai, H. Brendan McMahan

We consider a the general online convex optimization framework introduced by Zinkevich. In this setting, there is a sequence of convex functions. Each period, we must choose a sign…