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05/25/2023
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization
Domain generalization (DG) is a prevalent problem in real-world applicat...
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04/24/2023
Universal Domain Adaptation via Compressive Attention Matching
Universal domain adaptation (UniDA) aims to transfer knowledge from the ...
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03/30/2023
Task-Oriented Multi-Modal Mutual Leaning for Vision-Language Models
Prompt learning has become one of the most efficient paradigms for adapt...
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11/17/2022
CAE v2: Context Autoencoder with CLIP Target
Masked image modeling (MIM) learns visual representation by masking and ...
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10/06/2022
Domain Generalization via Contrastive Causal Learning
Domain Generalization (DG) aims to learn a model that can generalize wel...
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08/07/2022
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization
Considerable progress has been made in domain generalization (DG) which ...
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02/27/2022
Attention-based Cross-Layer Domain Alignment for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims to learn transferable knowledg...
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10/13/2021
Do We Need to Directly Access the Source Datasets for Domain Generalization?
Domain generalization (DG) aims to learn a generalizable model from mult...
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10/04/2021
Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization
Domain generalization (DG) aims to learn from multiple source domains a ...
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10/02/2021
Domain-Specific Bias Filtering for Single Labeled Domain Generalization
Domain generalization (DG) utilizes multiple labeled source datasets to ...
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07/13/2021
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition
Instrumental variables (IVs), sources of treatment randomization that ar...
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06/12/2020
Learning Decomposed Representation for Counterfactual Inference
One fundamental problem in the learning treatment effect from observatio...
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03/21/2019
