Abstract—The state of the art metric learning algorithms cannot perform well for domain adaptation settings, such as cross-domain face recognition,�...
Apr 5, 2011 � In this paper, we propose the domain adaptation metric learning (DAML), by introducing a data-dependent regularization to the conventional�...
This paper proposes the domain adaptation metric learning (DAML), by introducing a data-dependent regularization to the conventional metric learning in the�...
In this paper, we propose the domain adaptation metric learning (DAML), by introducing a data-dependent regularization to the conventional metric learning in�...
Jun 8, 2019 � DAML is an end-to-end trainable dialog system model that learns from multiple rich-resource tasks and then adapts to new domains with minimal�...
Missing: Metric | Show results with:Metric
Jul 12, 2022 � The projection matrix learned by DAML-ESI is used to eliminate the distribution differences between different domains, and the distance metric�...
Jun 25, 2024 � Distance metric learning (DML) aims to find an appropriate way to reveal the underlying data relationship. It is critical in many machine�...
Jul 10, 2022 � In this paper, we proposed the DAML training method to solve the domain shift problem in TST and pro- posed a new TST model architecture named�...
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The domain adaptation metric learning. (DAML) approach presented in [19] is able to learn non- linear target metric based on the kernel method. Recently, neural�...
we propose a new meta learning training strategy. 072 named domain adaptive meta learning (DAML). 073. Different from MAML, DAML adopts a domain. 074 adaptive�...