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Found 6 papers, 1 papers with code
A Pre-trained Sequential Recommendation Framework: Popularity Dynamics for Zero-shot Transfer
In addition, with a simple post-hoc interpolation, PrepRec can improve the performance of existing sequential recommenders on average by 13. 8\% in Recall@10 and 29. 5% in NDCG@10.
Experimental Results of Underwater Sound Speed Profile Inversion by Few-shot Multi-task Learning
Underwater Sound Speed Profile (SSP) distribution has great influence on the propagation mode of acoustic signal, thus the fast and accurate estimation of SSP is of great importance in building underwater observation systems.
Underwater Sound Speed Profile Construction: A Review
The proposal of SSP inversion method greatly improves the convenience and real--time performance, but the accuracy is not as good as the direct measurement method.
Pre-trained Neural Recommenders: A Transferable Zero-Shot Framework for Recommendation Systems
Thus, we use the statistical characteristics of the user-item interaction matrix to identify dataset-independent representations for users and items.
Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
We present InfoMotif, a new semi-supervised, motif-regularized, learning framework over graphs.
An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms
We develop a novel induced relational graph convolutional network (IR-GCN) framework to address the question.
