7 citations · 7 across the 8 of their papers we have counts for
4 papers · 1 filter
An Overview of Low-Rank Structures in the Training and Adaptation of Large Models
Laura Balzano, Tianjiao Ding, Benjamin D. Haeffele +5
The substantial computational demands of modern large-scale deep learning present significant challenges for efficient training and deployment. Recent research has revealed a wides…
Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction
Ziyang Wu, Tianjiao Ding, Yifu Lu +6
The attention operator is arguably the key distinguishing factor of transformer architectures, which have demonstrated state-of-the-art performance on a variety of tasks. However,…
Unsupervised Manifold Linearizing and Clustering
Tianjiao Ding, Shengbang Tong, Kwan Ho Ryan Chan +3
We consider the problem of simultaneously clustering and learning a linear representation of data lying close to a union of low-dimensional manifolds, a fundamental task in machine…
Efficient Maximal Coding Rate Reduction by Variational Forms
Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan +3
The principle of Maximal Coding Rate Reduction (MCR) has recently been proposed as a training objective for learning discriminative low-dimensional structures intrinsic to high…