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Št. zadetkov: 2
Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions
Tengyuan Liang
Video in druga učna gradiva
Oznake: computer science;machine learning;active learning;computational learning theory;on-line learning;reinforcement learning;semi-supervised learning
We consider the problem of optimizing an approximately convex function over a bounded convex set in $\mathbb{R}^n$ using only function evaluations. The problem is reduced to sampling from an \emph{approximately} log-concave distribution using the Hit-and-Run method, with query complexity of $\mathca ...
Leto: 2015 Vir: videolectures.net
Learning with Square Loss: Localization through Offset Rademacher Complexity
Tengyuan Liang
Video in druga učna gradiva
Oznake: computer science;machine learning;active learning;computational learning theory;on-line learning;reinforcement learning;semi-supervised learning
We consider regression with square loss and general classes of functions without the boundedness assumption. We introduce a notion of offset Rademacher complexity that provides a transparent way to study localization both in expectation and in high probability. For any (possibly non-convex) class, t ...
Leto: 2015 Vir: videolectures.net
Št. zadetkov: 2
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