图 书 馆
快速的支持向量机的训练与分类上的图形处理器Fast Support Vector Machine Training and Classification on Graphics Processors |
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| 课程网址: | http://videolectures.net/icml08_catanzaro_fsvm/ |
| 主讲教师: | Bryan Catanzaro |
| 开课单位: | 加州大学 |
| 开课时间: | 2008-08-05 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Recent developments in programmable, highly parallel Graphics Processing Units (GPUs) have enabled high performance implementations of machine learning algorithms. We describe a solver for Support Vector Machine training, using Platt's Sequential Minimal Optimization algorithm and an adaptive first and second order working set selection heuristic, which achieves speedups of 9-35x over LIBSVM running on a traditional processor. We also present a GPU-based system for SVM classification which achieves speedups of 81-138x over LibSVM (5-24x over our own CPU-based SVM classifier). |
| 关 键 词: | 图形处理单元; 向量机训练; 最小优化算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：吴雨秋(课程编辑志愿者) |
| 阅读次数: | 56 |