图 书 馆
结构化稀疏诱导范数的有效集算法Active Set Algorithm for Structured Sparsity-Inducing Norm |
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| 课程网址: | http://videolectures.net/nipsworkshops09_jenatton_asa/ |
| 主讲教师: | Rodolphe Jenatton |
| 开课单位: | 法国国家信息与自动化研究所 |
| 开课时间: | 2010-01-19 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider the empirical risk minimization problem for linear supervised learning, with regularization by structured sparsity-inducing norms. These are defined as sums of Euclidean norms on certain subsets of variables, extending the usual ℓ1-norm and the group ℓ1-norm by allowing the subsets to overlap. This leads to a specific set of allowed nonzero patterns for the solutions of such problems. We first explore the relationship between the groups defining the norm and the resulting nonzero patterns. In particular, we show how geometrical information about the variables can be encoded by our regularization. We finally present an active set algorithm to efficiently solve the corresponding minimization problem. |
| 关 键 词: | 结构化稀疏; 诱导规范; 非零模式; 最小化问题 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-01-15：yumf |
| 阅读次数: | 130 |