activity
20192023
most citedLearning N:M Fine-grained Structured Sparse Neural Networks From Scratch

74 citations · 164 across the 14 of their papers we have counts for

collaborators
Showing 2021Show all

7 papers · 1 filter

cs.DC2021★ 12 cited

BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning

Bicheng Ying, Kun Yuan, Hanbin Hu +2

Decentralized algorithm is a form of computation that achieves a global goal through local dynamics that relies on low-cost communication between directly-connected agents. On larg…

cs.CV2021

Self-supervised Correlation Mining Network for Person Image Generation

Zijian Wang, Xingqun Qi, Kun Yuan +1

Person image generation aims to perform non-rigid deformation on source images, which generally requires unaligned data pairs for training. Recently, self-supervised methods expres…

cs.DC2021★ 51 cited

A Unified and Refined Convergence Analysis for Non-Convex Decentralized Learning

Sulaiman A. Alghunaim, Kun Yuan

We study the consensus decentralized optimization problem where the objective function is the average of agents private non-convex cost functions; moreover, the agents can only…

cs.CV2021★ 5 cited

Effective Model Sparsification by Scheduled Grow-and-Prune Methods

Xiaolong Ma, Minghai Qin, Fei Sun +7

Deep neural networks (DNNs) are effective in solving many real-world problems. Larger DNN models usually exhibit better quality (e.g., accuracy) but their excessive computation res…

cs.CV2021★ 5 cited

Incorporating Convolution Designs into Visual Transformers

Kun Yuan, Shaopeng Guo, Ziwei Liu +3

Motivated by the success of Transformers in natural language processing (NLP) tasks, there emerge some attempts (e.g., ViT and DeiT) to apply Transformers to the vision domain. How…

cs.CV2021

Differentiable Network Adaption with Elastic Search Space

Shaopeng Guo, Yujie Wang, Kun Yuan +1

In this paper we propose a novel network adaption method called Differentiable Network Adaption (DNA), which can adapt an existing network to a specific computation budget by adjus…

cs.CV2021★ 74 cited

Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Aojun Zhou, Yukun Ma, Junnan Zhu +5

Sparsity in Deep Neural Networks (DNNs) has been widely studied to compress and accelerate the models on resource-constrained environments. It can be generally categorized into uns…