Learning in brains and machines

被引：3
|
作者：
Poggio, T [1 ]
Shelton, CR [1 ]
机构：
[1] MIT, Ctr Biol & Computat Learning, Cambridge, MA 02139 USA
来源：
SPATIAL VISION | 2000年 / 13卷 / 2-3期
关键词：
D O I：
10.1163/156856800741108
中图分类号：
Q6 [生物物理学];
学科分类号：
071011 ;
摘要：
The problem of learning is arguably at the very core of the problem of intelligence, both biological and artificial. In this paper we sketch some of our work over the last ten years in the area of supervised learning, focusing on three interlinked directions of research: theory, engineering applications (that is, making intelligent software) and neuroscience (that is, understanding the brain's mechanisms of learning).
引用
收藏
页码：287 / 296
页数：10
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