小秋SLAM笔记

This paper proposes a new method to weight subspaces in feature groups and individual features for clustering high-dimensional data. In this method, the features of high-dimensional data are divided into feature groups, based on their natural characteristics. Two types of weights are introduced to the clustering process to simultaneously identify the importance of feature groups and individual features in each cluster. A new optimization model is given to define the optimization process and a ne

test-LC_Group-.net-mvc-microservices Тестовоезадание。 КLC集团。 ASP.NET MVC +微服务。

Sparse coding and dictionary learning with class-specific group sparsity

1.2.0 支持系统托盘 和 快捷操作 https://blog.csdn.net/kcp606/article/details/113742287

支持系统托盘 和 快捷操作，增加反馈地址 https://blog.csdn.net/kcp606/article/details/113742287

1.1 版本，支持系统托盘 https://blog.csdn.net/kcp606/article/details/113742287

hosts 切换软件 https://blog.csdn.net/kcp606/article/details/113742287

使用maven构建多模块项目，包含spring boot子模块和dao层

MySQL Group Replication官方文档-MGR中文版