图 书 馆
利用计算图进行大规模分布式机器学习Exploiting the Computation Graph for Large Scale Distributed Machine Learning |
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| 课程网址: | https://videolectures.net/videos/kdd2016_vishwanathan_machine_lea... |
| 主讲教师: | S.V.N. Vishwanathan |
| 开课单位: | KDD 2016研讨会 |
| 开课时间: | 2016-10-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Many machine learning algorithms minimize a regularized risk. It is well known that stochastic optimization algorithms are both theoretically and practically well motivated for regularized risk minimization. Unfortunately, stochastic optimization is not easy to parallelize. In this talk, we take a radically new approach and show that working with the saddle-point problem that arises out of the Lagrangian has a very specific computational graph structure which can be exploited to allow for a natural partitioning of the parameters across multiple processors. This allows us to derive a new parallel stochastic optimization algorithm for regularized risk minimization. Joint work with: Inderjit Dhillon, Cho-Jui Hsieh, Shihao Ji, Shin Matsushima, Parameshwaran Raman, Hsiang-Fu Yu, and Hyokun Yun. |
| 关 键 词: | 计算图; 分布式; 机器学习 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-01-07：liyq |
| 最后编审: | 2025-01-07：liyq |
| 阅读次数: | 8 |