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Partial Domain Adaptation

Partial Domain Adaptation is a transfer learning paradigm, which manages to transfer relevant knowledge from a large-scale source domain to a small-scale target domain.

Source: Deep Residual Correction Network for Partial Domain Adaptation

Papers

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Showing 1–50 of 56 papers

TitleStatusHype
Adversarial Reweighting for Partial Domain AdaptationCode1
Improving Mini-batch Optimal Transport via Partial TransportationCode1
Universal Domain Adaptation through Self SupervisionCode1
OneRing: A Simple Method for Source-free Open-partial Domain AdaptationCode1
A Balanced and Uncertainty-aware Approach for Partial Domain AdaptationCode1
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain AdaptationCode1
Learning to Transfer Examples for Partial Domain AdaptationCode1
Bi-level Unbalanced Optimal Transport for Partial Domain Adaptation—0
Class Conditional Alignment for Partial Domain Adaptation—0
Controlled Generation of Unseen Faults for Partial and Open-Partial Domain Adaptation—0
Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation—0
Discriminative Cross-Domain Feature Learning for Partial Domain Adaptation—0
Discriminative Partial Domain Adversarial Network—0
Domain Adversarial Reinforcement Learning for Partial Domain Adaptation—0
Domain-Invariant Feature Alignment Using Variational Inference For Partial Domain Adaptation—0
Discriminative Clustering for Robust Unsupervised Domain Adaptation—0
Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation—0
Adversarial Consistent Learning on Partial Domain Adaptation of PlantCLEF 2020 Challenge—0
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods—0
A Robust Negative Learning Approach to Partial Domain Adaptation Using Source Prototypes—0
Associative Partial Domain Adaptation—0
A Unified Framework for Unsupervised Domain Adaptation based on Instance Weighting—0
Partial Feature Selection and Alignment for Multi-Source Domain Adaptation—0
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network—0
Relation Adversarial Network for Low Resource Knowledge Graph Completion—0
Robust Class-Conditional Distribution Alignment for Partial Domain Adaptation—0
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation—0
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation—0
Self-Adaptive Partial Domain Adaptation—0
Self-Supervised Learning Across Domains—0
Soft-Masked Semi-Dual Optimal Transport for Partial Domain Adaptation—0
Tackling Partial Domain Adaptation with Self-Supervision—0
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning—0
TWINs: Two Weighted Inconsistency-reduced Networks for Partial Domain Adaptation—0
Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization—0
Co-training partial domain adaptation networks for industrial Fault Diagnosis—0
Learning Target Domain Specific Classifier for Partial Domain Adaptation—0
Low-Cost On-device Partial Domain Adaptation (LoCO-PDA): Enabling efficient CNN retraining on edge devices—0
MOT: Masked Optimal Transport for Partial Domain Adaptation—0
On Evolving Attention Towards Domain Adaptation—0
Partial Distribution Matching via Partial Wasserstein Adversarial Networks—0
Partial Domain Adaptation Using Graph Convolutional Networks—0
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation—0
Implicit Semantic Response Alignment for Partial Domain AdaptationCode0
Importance Weighted Adversarial Nets for Partial Domain AdaptationCode0
Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain AdaptationCode0
Selective Partial Domain AdaptationCode0
Learning to Discover Knowledge: A Weakly-Supervised Partial Domain Adaptation ApproachCode0
From Big to Small: Adaptive Learning to Partial-Set DomainsCode0
Minimum Class Confusion for Versatile Domain AdaptationCode0
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