incontinence
发表于 2025-3-28 16:13:36
Delia Davine a novel loss function that encourages the target dataset’s embeddings to form clusters. While ADDA and M-ADDA use similar architectures, we show that M-ADDA performs significantly better on the digits adaptation datasets of MNIST and USPS. This suggests that using metric learning for domain adapta
Ringworm
发表于 2025-3-28 21:59:47
Delia Davine a novel loss function that encourages the target dataset’s embeddings to form clusters. While ADDA and M-ADDA use similar architectures, we show that M-ADDA performs significantly better on the digits adaptation datasets of MNIST and USPS. This suggests that using metric learning for domain adapta
改革运动
发表于 2025-3-29 00:10:39
Delia Davinthe reuse of source domain data is .. As a solution, we extend recent techniques based on . and their ., both considering supervised and unsupervised domain adaptation settings. The proposed models are tested and compared on private and publicly available source datasets showing significant performa
WITH
发表于 2025-3-29 05:19:35
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