图 书 馆
生成相似模型的多任务化Multi-task Regularization of Generative Similarity Models |
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| 课程网址: | http://videolectures.net/simbad2011_cazzanti_generative/ |
| 主讲教师: | Luca Cazzanti |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2011-10-17 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We investigate a multi-task approach to similarity discriminant analysis, where we propose treating the estimation of the different class-conditional distributions of the pairwise similarities as multiple tasks. We show that regularizing these estimates together using a least-squares regularization weighted by a task-relatedness matrix can reduce the resulting maximum a posteriori classification errors. Results are given for benchmark data sets spanning a range of applications. In addition, we present a new application of similarity-based learning to analyzing the rhetoric of multiple insurgent groups in Iraq. We show how to produce the necessary task relatedness information from standard given training data, as well as how to derive task-relatedness information if given side information about the class relatedness. |
| 关 键 词: | 相似性判别分析; 基准数据集; 后验概率 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-01：吴雨秋(课程编辑志愿者) |
| 阅读次数: | 55 |