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On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization
Published on Aug 09, 20133072 Views
The problem of stochastic convex optimization with bandit feedback (in the learning community) or without knowledge of gradients (in the optimization community) has received much attention in recent y
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On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization00:00
Bandit / Derivative-Free Stochastic Convex Optimization - 100:01
Bandit / Derivative-Free Stochastic Convex Optimization - 200:37
Attainable Performance - 102:00
Attainable Performance - 202:35
Our Results - 104:24
Our Results - 205:29
Our Results - 306:55
Quadratic Functions: Upper Bounds - 107:19
Quadratic Functions: Upper Bounds - 208:02
Quadratic Functions: Upper Bounds - 308:55
Quadratic Functions: Upper Bounds - 409:32
Quadratic Functions: Lower Bounds10:12
Proof Idea10:40
Quadratic Functions: Lower Bounds11:42
Strongly Convex and Smooth Functions13:03
Summary14:25