Provable nonconvex optimization in signal processing and machine learning

来源 :2016数学青年学者论坛(2016 Young Mathematician Forum) | 被引量 : 0次 | 上传用户：yuan002003

【摘要】

：

　　Nonconvex optimization methods arise naturally in various fields related to high-dimensional data.In nonlinear signal processing,least squares fitting resul

【作者】

：

Xiaodong Li

【机构】

：

UniversityofCalifornia,Davis

【出处】

：

2016数学青年学者论坛(2016 Young Mathematician Forum)

【发表日期】

：

2016年12期

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　　Nonconvex optimization methods arise naturally in various fields related to high-dimensional data.In nonlinear signal processing,least squares fitting results in nonconvex optimization; in sensor network localization and manifold learning,fitting to the local distance information leads to nonconvex optimization.However,theoretical properties of nonconvex optimization have not been well explored due to potential local minima.

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Provable nonconvex optimization in signal processing and machine learning

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