activity
20202022
most citedEfficient Test-Time Model Adaptation without Forgetting

66 citations · 110 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG202266 cited

Efficient Test-Time Model Adaptation without Forgetting

Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang +4

Test-time adaptation (TTA) seeks to tackle potential distribution shifts between training and testing data by adapting a given model w.r.t. any testing sample. This task is particu…

cs.CV2021

Content-Aware Convolutional Neural Networks

Yong Guo, Yaofo Chen, Mingkui Tan +3

Convolutional Neural Networks (CNNs) have achieved great success due to the powerful feature learning ability of convolution layers. Specifically, the standard convolution traverse…

cs.CV20215 cited

Contrastive Neural Architecture Search with Neural Architecture Comparators

Yaofo Chen, Yong Guo, Qi Chen +4

One of the key steps in Neural Architecture Search (NAS) is to estimate the performance of candidate architectures. Existing methods either directly use the validation performance…

cs.LG20214 cited

Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets

Yong Guo, Yaofo Chen, Yin Zheng +5

Designing feasible and effective architectures under diverse computation budgets incurred by different applications/devices is essential for deploying deep models in practice. Exis…

cs.CV202035 cited

Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search

Yong Guo, Yaofo Chen, Yin Zheng +4

Neural architecture search (NAS) has become an important approach to automatically find effective architectures. To cover all possible good architectures, we need to search in an e…