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Found 5 papers, 3 papers with code
Recommender Transformers with Behavior Pathways
We conclude this characteristic for sequential behaviors of each user as the Behavior Pathway.
MAMDR: A Model Agnostic Learning Method for Multi-Domain Recommendation
We integrate these components into a unified framework and present MAMDR, which can be applied to any model structure to perform multi-domain recommendation.
Progressive Adversarial Networks for Fine-Grained Domain Adaptation
Fine-grained visual categorization has long been considered as an important problem, however, its real application is still restricted, since precisely annotating a large fine-grained image dataset is a laborious task and requires expert-level human knowledge.
Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning
Before sufficient training data is available, fine-tuning neural networks pre-trained on large-scale datasets substantially outperforms training from random initialization.
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation
In this paper, a series of experiments based on spectral analysis of the feature representations have been conducted, revealing an unexpected deterioration of the discriminability while learning transferable features adversarially.
