图 书 馆
Infer.NET - 实际问题实施和近似技术的比较Infer.NET - Practical Implementation Issues and a Comparison of Approximation Techniques |
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| 课程网址: | http://videolectures.net/abi07_winn_ipi/ |
| 主讲教师: | John Winn |
| 开课单位: | 微软公司 |
| 开课时间: | 2007-12-31 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Infer.NET is an efficient, general-purpose inference engine developed at Microsoft Cambridge by Tom Minka, John Winn and others. It aims to be highly efficient, general purpose and extensible --- three normally contradictory goals. We have largely managed to achieve these goals using a compiler-like architecture, so that code is generated to perform the desired inference task. Infer.NET can apply one of a range of inference algorithms to a given probabilistic model, and so provides a useful framework for comparing the performance of different algorithms. In this talk, I will describe the capabilities and infrastructure of Infer.NET and give examples of applying both expectation propagation and variational message passing on the same model. I will also describe some failure cases that we have encountered for each algorithm. |
| 关 键 词: | 近似技术; 软件开发; 计算机应用 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-04-14：chenxin |
| 阅读次数: | 38 |