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On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization
Published on 2013-01-162807 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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Presentation
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization00:00
Bandit / Derivative-Free Stochastic Convex Optimization (1)00:00
Bandit / Derivative-Free Stochastic Convex Optimization (2)00:29
Attainable Performance (1)02:01
Attainable Performance (2)02:47
Attainable Performance (3)02:51
Attainable Performance (4)03:07
Attainable Performance (5)03:30
Our Results (1)04:16
Our Results (2)04:41
Our Results (3)05:02
Our Results (4)05:57
Our Results (5)06:35
Quadratic Functions: Upper Bounds (1)06:53
Quadratic Functions: Upper Bounds (2)07:41
Quadratic Functions: Upper Bounds (3)10:25
Quadratic Functions: Upper Bounds (4)11:19
Quadratic Functions: Lower Bounds (1)12:02
Proof Idea12:29
Quadratic Functions: Lower Bounds (2)13:08
Strongly Convex and Smooth Functions15:10
Summary16:26