图 书 馆
学习深度结构化模型Learning Deep Structured Models |
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| 课程网址: | http://videolectures.net/icml2015_chen_deep_structured_models/ |
| 主讲教师: | Liang-Chieh Chen |
| 开课单位: | 加州大学洛杉矶分校 |
| 开课时间: | 2015-09-27 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Many problems in real-world applications involve predicting several random variables that are statistically related. Markov random fields (MRFs) are a great mathematical tool to encode such dependencies. The goal of this paper is to combine MRFs with deep learning to estimate complex representations while taking into account the dependencies between the output random variables. Towards this goal, we propose a training algorithm that is able to learn structured models jointly with deep features that form the MRF potentials. Our approach is efficient as it blends learning and inference and makes use of GPU acceleration. We demonstrate the effectiveness of our algorithm in the tasks of predicting words from noisy images, as well as tagging of Flickr photographs. We show that joint learning of the deep features and the MRF parameters results in significant performance gains. |
| 关 键 词: | 随机变量; 深度学习; 依赖关系 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-07-19：chenxin01 |
| 最后编审: | 2023-07-19：chenxin01 |
| 阅读次数: | 29 |