科学研究
学术报告
当前位置: 学院主页 > 科学研究 > 学术报告 > 正文

Pretrained Transform-Based Tensor Representations

发布时间:2026-08-25 作者: 浏览次数:
Speaker: 赵熙乐 DateTime: 2026年8月28日(周五)上午10:00-11:00
Brief Introduction to Speaker:

赵熙乐,电子科技大学

Place: 新文科楼4楼413会议室
Abstract:Recently, Fourier transform-based tensor representations have been  suggested for processing and analyzing multi-dimensional data arising from real-world applications, where transform and the corresponding latent tensor serve as the two building blocks of this framework. From both perspectives, this talk will review recent progress in transform-based tensor representations. On one hand, we will discuss the evolution of the transform from linear and shallow ones to nonlinear and deep ones. On the other hand, we will discuss the evolution of the corresponding latent tensor from shallow and untrained ones to deep and pretrained ones Finally, we will also discuss the limitations and future possibilities of the transform-based tensor representation.