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特征空间中的指数族

Exponential Families in Feature Space
课程网址: http://videolectures.net/mlss04_smola_effs/  
主讲教师: Smola Alexander J
开课单位: 亚马逊公司
开课时间: 2007-02-25
课程语种: 英语
中文简介:
在本课程中,我将讨论指数族(统计学中的一种标准工具)如何在机器学习方面取得巨大成功,从而统一许多现有的算法,并轻而易举地发明新的算法。特别是,我将展示如何在特征空间中使用它们来恢复高斯过程分类,用于多类识别、序列注释(通过条件随机字段),以及它们如何通过异方差噪声假设导致高斯过程回归。
课程简介: In this course I will discuss how exponential families, a standard tool in statistics, can be used with great success in machine learning to unify many existing algorithms and to invent novel ones quite effortlessly. In particular, I will show how they can be used in feature space to recover Gaussian Process classification for multiclass discrimination, sequence annotation (via Conditional Random Fields), and how they can lead to Gaussian Process Regression with heteroscedastic noise assumptions.
关 键 词: 指数家庭; 机器学习; 特征空间; 分类多类判别; 序列注释
课程来源: 视频讲座网
最后编审: 2020-06-01:wuyq
阅读次数: 28