| 1. | Multi - instance learning from supervised view
从监督视角进行多示例学习 |
| 2. | An experimental study on mathematics learning from example and by doing
小学生数学示例学习的信息加工过程实验研究 |
| 3. | Design and application of a fuzzy classified rule based on learning from fuzzy examples
基于模糊示例学习的蠓虫分类规则的设计 |
| 4. | Changes of representation for efficient learning in structural domains . in proc . the 13th int
该问题对多示例学习领域的发展起到了推动作用。 |
| 5. | You can use the samples to learn about report design , data retrieval , and how to work with the report authoring tools
您可以使用示例学习如何设计报表、检索数据以及如何使用报表创作工具。 |
| 6. | I introduce the different stages of aop adoption and offer examples of learning applications and guidelines for success at each stage
我介绍了采用aop的不同阶段，并提供了示例学习应用程序和成功完成每个阶段的指南。 |
| 7. | Then the background theory of wll is given , including constructing and elaborating of condition ( cec ) and lbp ( lfetps based on production )
文章第二部分接着介绍了示例学习网上课程的理论基础：基于产生式表示的示例学习和条件建构-优化理论。 |
| 8. | In multi - instance learning , the training set comprises labeled bags that are composed of unlabeled instances , and the task is to predict the labels of unseen bags
在多示例学习中，训练样本是由多个示例组成的包，包是有概念标记的，但示例本身却没有概念标记。 |
| 9. | Journal of machine learning research , 2004 , 5 : 913 - 939 . 16 dempster a p , laird n m , rubin d b . maximum likelihood from incomplete data via the em algorithm
这个一般性的法则揭示了多示例学习与监督学习之间的联系，为多示例学习算法的设计提供了一种通用的途径。 |
| 10. | In this dissertation , after the learning from examples is briefly reviewed , a kind of fuzzy controller based on fuzzy learning from examples is proposed
本文以示例学习为基础，针对基本模糊控制器依赖人为经验的局限性，提出了一种基于模糊示例学习的模糊控制器。 |
