Browse > Methodology > Domain Adaptation > Unsupervised Domain Adaptation

Unsupervised Domain Adaptation

64 papers with code ยท Methodology
Subtask of Domain Adaptation

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Multi-Step Decentralized Domain Adaptation

ICLR 2020

Despite the recent breakthroughs in unsupervised domain adaptation (uDA), no prior work has studied the challenges of applying these methods in practical machine learning scenarios.

UNSUPERVISED DOMAIN ADAPTATION

Domain Adaptive Multiflow Networks

ICLR 2020

We tackle unsupervised domain adaptation by accounting for the fact that different domains may need to be processed differently to arrive to a common feature representation effective for recognition.

UNSUPERVISED DOMAIN ADAPTATION

Unsupervised Domain Adaptation through Self-Supervision

ICLR 2020

This paper addresses unsupervised domain adaptation, the setting where labeled training data is available on a source domain, but the goal is to have good performance on a target domain with only unlabeled data.

UNSUPERVISED DOMAIN ADAPTATION

The Role of Embedding Complexity in Domain-invariant Representations

ICLR 2020

In this work, we study, theoretically and empirically, the effect of the embedding complexity on generalization to the target domain.

UNSUPERVISED DOMAIN ADAPTATION

Unsupervised domain adaptation with imputation

ICLR 2020

Motivated by practical applications, we consider unsupervised domain adaptation for classification problems, in the presence of missing data in the target domain.

IMPUTATION UNSUPERVISED DOMAIN ADAPTATION

Open-Set Domain Adaptation with Category-Agnostic Clusters

ICLR 2020

A clustering branch is capitalized on to ensure that the learnt representation preserves such underlying structure by matching the estimated assignment distribution over clusters to the inherent cluster distribution for each target sample.

UNSUPERVISED DOMAIN ADAPTATION

Unsupervised Domain Adaptation Meets Offline Recommender Learning

16 Oct 2019

To construct a well-performing recommender offline, eliminating selection biases of the rating feedback is critical.

UNSUPERVISED DOMAIN ADAPTATION

Learning Generalisable Omni-Scale Representations for Person Re-Identification

15 Oct 2019

An effective person re-identification (re-ID) model should learn feature representations that are both discriminative, for distinguishing similar-looking people, and generalisable, for deployment across datasets without any adaptation.

PERSON RE-IDENTIFICATION UNSUPERVISED DOMAIN ADAPTATION

A General Upper Bound for Unsupervised Domain Adaptation

3 Oct 2019

In this work, we present a novel upper bound of target error to address the problem for unsupervised domain adaptation.

IMAGE CLASSIFICATION UNSUPERVISED DOMAIN ADAPTATION

Domain Adaptation for Semantic Segmentation with Maximum Squares Loss

30 Sep 2019

However, when applying the entropy minimization to UDA for semantic segmentation, the gradient of the entropy is biased towards samples that are easy to transfer.

SEMANTIC SEGMENTATION UNSUPERVISED DOMAIN ADAPTATION