How Sparse Can We Prune A Deep Network: A Geometric Viewpoint

1 code implementation • 9 Jun 2023 • Qiaozhe Zhang, Ruijie Zhang, Jun Sun, Yingzhuang Liu

To address this problem, in this work we take a first principles approach, specifically, by merely enforcing the sparsity constraint on the original loss function, we're able to characterize the sharp phase transition point of pruning ratio, which corresponds to the boundary between the feasible and the infeasible, from the perspective of high-dimensional geometry.

Network Pruning

Multi-level Multiple Instance Learning with Transformer for Whole Slide Image Classification

1 code implementation • 8 Jun 2023 • Ruijie Zhang, Qiaozhe Zhang, Yingzhuang Liu, Hao Xin, Yan Liu, Xinggang Wang

Whole slide image (WSI) refers to a type of high-resolution scanned tissue image, which is extensively employed in computer-assisted diagnosis (CAD).

Image Classification Multiple Instance Learning +1

A Range-Null Space Decomposition Approach for Fast and Flexible Spectral Compressive Imaging

1 code implementation • 16 May 2023 • Junyu Wang, Shijie Wang, Ruijie Zhang, Zengqiang Zheng, Wenyu Liu, Xinggang Wang

We present RND-SCI, a novel framework for compressive hyperspectral image (HSI) reconstruction.