图 书 馆
图的深度学习Deep Learning on Graphs |
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| 课程网址: | http://videolectures.net/solomon_leskovec_deep_learning/ |
| 主讲教师: | Jure Leskovec |
| 开课单位: | 斯坦福大学 |
| 开课时间: | 2019-06-17 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Machine learning on graphs is an important and ubiquitous task with applications ranging from drug design to friendship recommendation in social networks. The primary challenge in this domain is finding a way to represent, or encode, graph structure so that it can be easily exploited by machine learning models. However, traditionally machine learning approaches relied on user-defined heuristics to extract features encoding structural information about a graph. In this talk I will discuss methods that automatically learn to encode graph structure into low-dimensional embeddings, using techniques based on deep learning and nonlinear dimensionality reduction. I will provide a conceptual review of key advancements in this area of representation learning on graphs, including random-walk based algorithms, and graph convolutional networks. We will discuss applications to web-scale recommender systems, healthcare and knowledge representation and reasoning. |
| 关 键 词: | 深度学习; 机器学习; 图形编码 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-27：yxd |
| 最后编审: | 2020-11-27：yxd |
| 阅读次数: | 46 |