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» Generalized Boosting Algorithms for Convex Optimization
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CORR
2004
Springer
103views Education» more  CORR 2004»
13 years 8 months ago
Online convex optimization in the bandit setting: gradient descent without a gradient
We study a general online convex optimization problem. We have a convex set S and an unknown sequence of cost functions c1, c2, . . . , and in each period, we choose a feasible po...
Abraham Flaxman, Adam Tauman Kalai, H. Brendan McM...
MOR
2006
81views more  MOR 2006»
13 years 8 months ago
Simulated Annealing for Convex Optimization
We apply the method known as simulated annealing to the following problem in convex optimization: minimize a linear function over an arbitrary convex set, where the convex set is ...
Adam Tauman Kalai, Santosh Vempala
CORR
2010
Springer
64views Education» more  CORR 2010»
13 years 8 months ago
Near-Optimal Evasion of Convex-Inducing Classifiers
Classifiers are often used to detect miscreant activities. We study how an adversary can efficiently query a classifier to elicit information that allows the adversary to evade de...
Blaine Nelson, Benjamin I. P. Rubinstein, Ling Hua...
FAW
2010
Springer
259views Algorithms» more  FAW 2010»
13 years 9 months ago
Adaptive Algorithms for Planar Convex Hull Problems
We study problems in computational geometry from the viewpoint of adaptive algorithms. Adaptive algorithms have been extensively studied for the sorting problem, and in this paper ...
Hee-Kap Ahn, Yoshio Okamoto
NIPS
2008
13 years 10 months ago
Mind the Duality Gap: Logarithmic regret algorithms for online optimization
We describe a primal-dual framework for the design and analysis of online strongly convex optimization algorithms. Our framework yields the tightest known logarithmic regret bound...
Shai Shalev-Shwartz, Sham M. Kakade