从技术角度看——没有窗格就没有收获

A. Hogan
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引用次数: 0

摘要

传统上,机器学习社区一直积极主动地为各种类型的数据开发技术,例如文本、音频、图像、视频、时间序列,当然还有矩阵、张量等。“那么图形呢?”我们中的一些图形爱好者可能会沮丧地问自己,然后把我们美丽的图形转换成一个野蛮的数字表,与它的母体没有什么相似之处,也没有它所代表的现象,但至少可以被纳入当时的机器学习框架。谢天谢地,这样的日子即将结束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Technical Perspective - No PANE, No Gain
The machine learning community has traditionally been proactive in developing techniques for diverse types of data, such as text, audio, images, videos, time series, and, of course, matrices, tensors, etc. "But what about graphs?" some of us graph enthusiasts may have asked ourselves, dejectedly, before transforming our beautiful graph into a brutalistic table of numbers that bore little resemblance to its parent, nor the phenomena it represented, but could at least be shovelled into the machine learning frameworks of the time. Thankfully those days are coming to an end.
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