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论结构性产出培训：难点和有效的替代方案On Structured Output Training: Hard Cases and an Efficient Alternative |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_gartner_sothcea/ |
| 主讲教师: | Thomas Gartner |
| 开课单位: | 国际原子能机构 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider a class of structured prediction problems for which the assumptions made by state-of-the-art algorithms fail. To deal with exponentially sized output sets, these algorithms assume, for instance, that the best output for a given input can be found efficiently. While this holds for many important real world problems, there are also many relevant and seemingly simple problems where these assumptions do not hold. In this paper, we consider route prediction, which is the problem of finding a cyclic permutation of some points of interest, as an example and show that state-of-the-art approaches cannot guarantee polynomial runtime for this output set. We then present a novel formulation of the learning problem that can be trained efficiently whenever a particular ’super-structure counting’ problem can be solved efficiently for the output set. We also list several output sets for which this assumption holds and report experimental results. |
| 关 键 词: | 结构化预测; 输出集; 超级结构计数 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-24：cwx |
| 阅读次数: | 79 |