稀疏算法不稳定：一个没有免费午餐的定理 ][Sparse Algorithms are Not Stable: A No-free-lunch Theorem]

稀疏算法不稳定：一个没有免费午餐的定理 Sparse Algorithms are Not Stable: A No-free-lunch Theorem


课程网址:	http://videolectures.net/nipsworkshops2012_xu_theorem/
主讲教师:	Huan Xu
开课单位:	新加坡国立大学
开课时间:	2013-01-16
课程语种:	英语
中文简介:	我们考虑机器学习中两个广泛使用的概念，即：稀疏性和稳定性。这两种观念都被认为是可取的，并且被认为可以带来良好的泛化能力。我们证明这两个概念相互矛盾：稀疏算法不能稳定，反之亦然。因此，必须在设计学习算法时权衡稀疏性和稳定性。这意味着，与\ ell_2正则化回归相比，\ ell_1正则化回归（Lasso）不能稳定。
课程简介:	We consider two widely used notions in machine learning, namely: sparsity and stability. Both notions are deemed desirable, and are believed to lead to good generalization ability. We show that these two notions contradict each other: a sparse algorithm can not be stable and vice versa. Thus, one has to tradeoff sparsity and stability in designing a learning algorithm. This implies that, in contrast to \ell_2 regularized regression, \ell_1 regularized regression (Lasso) cannot be stable.
关键词:	机器学习; 稀疏算法; 学习算法
课程来源:	视频讲座网
最后编审:	2019-09-08：lxf
阅读次数:	51

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