图 书 馆
多层网络损失面分布图The landscape of the loss surfaces of multilayer networks |
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| 课程网址: | http://videolectures.net/colt2015_choromanska_multilayer_networks... |
| 主讲教师: | Anna Choromanska |
| 开课单位: | 视频讲座网 |
| 开课时间: | 2015-08-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Deep learning has enjoyed a resurgence of interest in the last few years for such applications as image and speech recognition, or natural language processing. The vast majority of practical applications of deep learning focus on supervised learning, where the supervised loss function is minimized using stochastic gradient descent. The properties of this highly non-convex loss function, such as its landscape and the behavior of critical points (maxima, minima, and saddle points), as well as the reason why large- and small-size networks achieve radically different practical performance, are however very poorly understood. It was only recently shown that new results in spin-glass theory potentially may provide an explanation for these problems by establishing a connection between the loss function of the neural networks and the Hamiltonian of the spherical spin-glass models. The connection between both models relies on a number of possibly unrealistic assumptions, yet the empirical evidence suggests that the connection may exist in real. The question we pose is whether it is possible to drop some of these assumptions to establish a stronger connection between both models. |
| 关 键 词: | 自然语言; 深度学习; 监督学习; 随机梯度 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-12-02：chenxin01 |
| 最后编审: | 2022-12-02：chenxin01 |
| 阅读次数: | 29 |