DisClusterDA

Reported on 4 benchmarks across 2 tasks · 2 papers · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology2 results

Domain AdaptationonVisDA2017
Average Accuracy· 2023-02-23
87.1
SOTA
Unsupervised Domain Adaptation via Distilled Discriminative Clustering arXiv:2302.11984
Domain AdaptationonOffice-Home
Average Accuracy· 2022-06-19
71.4
best: 90.6 (MoA (OpenCLIP, ViT-B/16))
0/1 Deep Neural Networks via Block Coordinate Descent arXiv:2206.09379

Other2 results

Unsupervised Domain AdaptationonVisDA2017
Average Accuracy· 2023-02-23
87.1
SOTA
Unsupervised Domain Adaptation via Distilled Discriminative Clustering arXiv:2302.11984
Unsupervised Domain AdaptationonOffice-Home
Average Accuracy· 2022-06-19
71.4
SOTA
0/1 Deep Neural Networks via Block Coordinate Descent arXiv:2206.09379