most citedNeural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective

51 citations · 79 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20223 cited

Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices

Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu +6

In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stre…

cs.LG20227 cited

Auto-scaling Vision Transformers without Training

Wuyang Chen, Wei Huang, Xianzhi Du +3

This work targets automated designing and scaling of Vision Transformers (ViTs). The motivation comes from two pain spots: 1) the lack of efficient and principled methods for desig…

cs.CV2021

Font Completion and Manipulation by Cycling Between Multi-Modality Representations

Ye Yuan, Wuyang Chen, Zhaowen Wang +4

Generating font glyphs of consistent style from one or a few reference glyphs, i.e., font completion, is an important task in topographical design. As the problem is more well-defi…

cs.CV202118 cited

Contrastive Syn-to-Real Generalization

Wuyang Chen, Zhiding Yu, Shalini De Mello +4

Training on synthetic data can be beneficial for label or data-scarce scenarios. However, synthetically trained models often suffer from poor generalization in real domains due to…

cs.CV202151 cited

Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective

Wuyang Chen, Xinyu Gong, Zhangyang Wang

Neural Architecture Search (NAS) has been explosively studied to automate the discovery of top-performer neural networks. Current works require heavy training of supernet or intens…

math.OC2021

Learning to Optimize: A Primer and A Benchmark

Tianlong Chen, Xiaohan Chen, Wuyang Chen +4

Learning to optimize (L2O) is an emerging approach that leverages machine learning to develop optimization methods, aiming at reducing the laborious iterations of hand engineering.…