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Found 5 papers, 3 papers with code
Tuning Pre-trained Model via Moment Probing
Distinguished from LP which builds a linear classification head based on the mean of final features (e. g., word tokens for ViT) or classification tokens, our MP performs a linear classifier on feature distribution, which provides the stronger representation ability by exploiting richer statistical information inherent in features.
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations
However, MTL research faces two challenges: 1) effectively modeling the relationships between tasks to enable knowledge sharing, and 2) jointly learning task-specific and shared knowledge.
DropCov: A Simple yet Effective Method for Improving Deep Architectures
Particularly, we for the first time show that \textit{effective post-normalization can make a good trade-off between representation decorrelation and information preservation for GCP, which are crucial to alleviate over-fitting and increase representation ability of deep GCP networks, respectively}.
Demand Response Method Considering Multiple Types of Flexible Loads in Industrial Parks
With the rapid development of the energy internet, the proportion of flexible loads in smart grid is getting much higher than before.
Hierarchical Classification of Pulmonary Lesions: A Large-Scale Radio-Pathomics Study
A three-level hierarchical classification system for pulmonary lesions is developed, which covers most diseases in cancer-related diagnosis.
