Mapping Energy Landscapes of Non-Convex Learning Problems

2 Oct 2014Maria PavlovskaiaKewei TuSong-Chun Zhu

In many statistical learning problems, the target functions to be optimized are highly non-convex in various model spaces and thus are difficult to analyze. In this paper, we compute \emph{Energy Landscape Maps} (ELMs) which characterize and visualize an energy function with a tree structure, in which each leaf node represents a local minimum and each non-leaf node represents the barrier between adjacent energy basins... (read more)

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