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Unsupervised Domain

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Maximum Classifier Discrepancy for Unsupervised Domain ...

Maximum Classifier Discrepancy for Unsupervised Domain ...

openaccess.thecvf.com

Maximum Classifier Discrepancy for Unsupervised Domain Adaptation Kuniaki Saito1, Kohei Watanabe1, Yoshitaka Ushiku1, and Tatsuya Harada1,2 1The University of Tokyo, 2RIKEN {k-saito,watanabe,ushiku,harada}@mi.t.u-tokyo.ac.jp Abstract In this work, we present a method for unsupervised do-

  Domain, Unsupervised, Unsupervised domain

FDA: Fourier Domain Adaptation for Semantic Segmentation

FDA: Fourier Domain Adaptation for Semantic Segmentation

openaccess.thecvf.com

In unsupervised domain adaptation (UDA), we are given a source dataset Ds = {(xs i,y s i) ∼ P(xs,ys)}N s i=1, where xs ∈ RH×W×3 is a color image, and ys ∈ RH×W is the semantic map associated with xs. Similarly D t={x i} N t i=1 is the target …

  Domain, Unsupervised, Unsupervised domain

Neural Discrete Representation Learning

Neural Discrete Representation Learning

arxiv.org

tasks such as few-shot learning [34], domain adaptation [17], or reinforcement learning [35] heavily rely on learnt representations from raw data, but the usefulness of generic representations trained in an unsupervised fashion is still far from being the dominant approach.

  Representation, Domain, Unsupervised

Language Models are Unsupervised Multitask Learners

Language Models are Unsupervised Multitask Learners

persagen.com

on single domain datasets is a major contributor to the lack of generalization observed in current systems. Progress towards robust systems with current architectures is likely to require training and measuring performance on a wide ... Language Models …

  Domain, Unsupervised

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