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Partial Domain Adaptation
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Soft-Masked Semi-Dual Optimal Transport for Partial Domain Adaptation
Co-training partial domain adaptation networks for industrial Fault Diagnosis
Partial Distribution Matching via Partial Wasserstein Adversarial Networks
Learning to Discover Knowledge: A Weakly-Supervised Partial Domain Adaptation Approach
A Unified Framework for Unsupervised Domain Adaptation based on Instance Weighting
Robust Class-Conditional Distribution Alignment for Partial Domain Adaptation
A Robust Negative Learning Approach to Partial Domain Adaptation Using Source Prototypes
Domain-Invariant Feature Alignment Using Variational Inference For Partial Domain Adaptation
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods
Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation
OneRing: A Simple Method for Source-free Open-partial Domain Adaptation
Controlled Generation of Unseen Faults for Partial and Open-Partial Domain Adaptation
From Big to Small: Adaptive Learning to Partial-Set Domains
Low-Cost On-device Partial Domain Adaptation (LoCO-PDA): Enabling efficient CNN retraining on edge devices
Self-Adaptive Partial Domain Adaptation
Partial Domain Adaptation without Domain Alignment
Improving Mini-batch Optimal Transport via Partial Transportation
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network
On Evolving Attention Towards Domain Adaptation
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation
Adversarial Consistent Learning on Partial Domain Adaptation of PlantCLEF 2020 Challenge
Unsupervised Domain Adaptation with Progressive Adaptation of Subspaces
Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation
Discriminative Cross-Domain Feature Learning for Partial Domain Adaptation
Learning Target Domain Specific Classifier for Partial Domain Adaptation
Associative Partial Domain Adaptation
Self-Supervised Learning Across Domains
Partial Domain Adaptation Using Graph Convolutional Networks
Deep Residual Correction Network for Partial Domain Adaptation
Class Conditional Alignment for Partial Domain Adaptation
A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Universal Domain Adaptation through Self Supervision
Minimum Class Confusion for Versatile Domain Adaptation
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