Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation

no code implementations • 23 Oct 2023 • Yongsong Huang, Wanqing Xie, Mingzhen Li, Mingmei Cheng, Jinzhou Wu, Weixiao Wang, Jane You, Xiaofeng Liu

However, the performance of FL can be constrained by the limited availability of labeled data in small institutes and the heterogeneous (i. e., non-i. i. d.)

Cardiac Segmentation Data Augmentation +2

FamilySeer: Towards Optimized Tensor Codes by Exploiting Computation Subgraph Similarity

no code implementations • 1 Jan 2022 • Shanjun Zhang, Mingzhen Li, Hailong Yang, Yi Liu, Zhongzhi Luan, Depei Qian

Currently, the DL compilers partition the input DL models into several subgraphs and leverage the auto-tuning to find the optimal tensor codes of these subgraphs.

The Deep Learning Compiler: A Comprehensive Survey

1 code implementation • 6 Feb 2020 • Mingzhen Li, Yi Liu, Xiaoyan Liu, Qingxiao Sun, Xin You, Hailong Yang, Zhongzhi Luan, Lin Gan, Guangwen Yang, Depei Qian

In this paper, we perform a comprehensive survey of existing DL compilers by dissecting the commonly adopted design in details, with emphasis on the DL oriented multi-level IRs, and frontend/backend optimizations.

swTVM: Towards Optimized Tensor Code Generation for Deep Learning on Sunway Many-Core Processor

no code implementations • 16 Apr 2019 • Mingzhen Li, Changxi Liu, Jianjin Liao, Xuegui Zheng, Hailong Yang, Rujun Sun, Jun Xu, Lin Gan, Guangwen Yang, Zhongzhi Luan, Depei Qian

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application portability.

Code Generation