12 citations · 12 across the 1 of their papers we have counts for
2 papers
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…
cs.LG2000
Noise-Tolerant Learning, the Parity Problem, and the Statistical Query Model
Avrim Blum, Adam Kalai, Hal Wasserman
We describe a slightly sub-exponential time algorithm for learning parity functions in the presence of random classification noise. This results in a polynomial-time algorithm for…