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Statistical Manifold and Entropy-Based Interence

2018-04-18 09:03    
主题:
Statistical Manifold and Entropy-Based Interence
时间:
2018-04-12 16:00-17:00
地点:
南开大学省身楼216教室
主讲人:
Zhang Jun

演讲内容介绍

    Information Geometry is the differential geometric study of the manifold of probability models, and promises to be a unifying geometric framework for investigating statistical inference, information theory, machine learning, etc. Instead of using metric for measuring distances on such manifolds, these applications often use "divergence functions" for measuring proximity of two points (that do not impose symmetry and triangular inequality). Divergence functions are tied to generalized entropy and cross-entropy functions widely used in machine learning and information sciences.

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