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Found 2 papers, 1 papers with code
Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems
As the deep learning techniques have expanded to real-world recommendation tasks, many deep neural network based Collaborative Filtering (CF) models have been developed to project user-item interactions into latent feature space, based on various neural architectures, such as multi-layer perceptron, auto-encoder and graph neural networks.
Prior-Knowledge and Attention-based Meta-Learning for Few-Shot Learning
In this paper, inspired by the human cognition process which utilizes both prior-knowledge and vision attention in learning new knowledge, we present a novel paradigm of meta-learning approach with three developments to introduce attention mechanism and prior-knowledge for meta-learning.
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