Dataset regeneration for sequential recommendation
The sequential recommender (SR) system is a crucial component of modern recommender
systems, as it aims to capture the evolving preferences of users. Significant efforts have …
systems, as it aims to capture the evolving preferences of users. Significant efforts have …
Improving diversity and discriminability based implicit contrastive learning for unsupervised domain adaptation
H Xu, C Shi, WZ Fan, Z Chen - Applied Intelligence, 2024 - Springer
In unsupervised domain adaptation (UDA), knowledge is transferred from label-rich source
domains to relevant but unlabeled target domains. Current most popular state-of-the-art …
domains to relevant but unlabeled target domains. Current most popular state-of-the-art …
Cbda: Contrastive-based data augmentation for domain generalization
Z Jiang, L Zhang, X Liang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the realm of domain generalization (DG), domain adversarial training is a popular method
for achieving invariant representations and is often applied to various tasks in this field …
for achieving invariant representations and is often applied to various tasks in this field …
Meta curvature-aware minimization for domain generalization
Domain generalization (DG) aims to enhance the ability of models trained on source
domains to generalize effectively to unseen domains. Recently, Sharpness-Aware …
domains to generalize effectively to unseen domains. Recently, Sharpness-Aware …
SETA: Semantic-Aware Token Augmentation for Domain Generalization
Domain generalization (DG) aims to enhance the model robustness against domain shifts
without accessing target domains. A prevalent category of methods for DG is data …
without accessing target domains. A prevalent category of methods for DG is data …
Advancing generalizable remote physiological measurement through the integration of explicit and implicit prior knowledge
Remote photoplethysmography (rPPG) is a promising technology that captures
physiological signals from face videos, with potential applications in medical health …
physiological signals from face videos, with potential applications in medical health …
Using cross-domain knowledge augmentation to explore comorbidity in electronic health records data
K Zhang, B Qian, X Zhang, Q Zheng - Expert Systems with Applications, 2025 - Elsevier
Research concentrating on specific diseases or employing single datasets, such as medical
histories and thematic data, has garnered considerable attention. However, there has been …
histories and thematic data, has garnered considerable attention. However, there has been …
SETA: Semantic-Aware Edge-Guided Token Augmentation for Domain Generalization
Domain generalization (DG) aims to enhance the model robustness against domain shifts
without accessing target domains. A prevalent category of methods for DG is data …
without accessing target domains. A prevalent category of methods for DG is data …
Graph convolutional network for adversarial domain generalization
X Zhang, H Su, X Liu - IEEE Transactions on Computational …, 2024 - ieeexplore.ieee.org
Domain generalization (DG) aims to create a model that is trained across multiple source
domains and is capable of performing well on new, previously unseen target domains. The …
domains and is capable of performing well on new, previously unseen target domains. The …
Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation
In recommendation systems, users frequently engage in multiple types of behaviors, such as
clicking, adding to cart, and purchasing. Multi-behavior sequential recommendation aims to …
clicking, adding to cart, and purchasing. Multi-behavior sequential recommendation aims to …