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Found 6 papers, 1 papers with code
Deep Active Learning for Anchor User Prediction
Due to the expensive costs of labeling anchor users for training prediction models, we consider in this paper the problem of minimizing the number of user pairs across multiple networks for labeling as to improve the accuracy of the prediction.
Modeling Text with Graph Convolutional Network for Cross-Modal Information Retrieval
A dual-path neural network model is proposed for couple feature learning in cross-modal information retrieval.
RLINK: Deep Reinforcement Learning for User Identity Linkage
User identity linkage is a task of recognizing the identities of the same user across different social networks (SN).
Cross-modal Knowledge Reasoning for Knowledge-based Visual Question Answering
Finally, we perform graph neural networks to infer the global-optimal answer by jointly considering all the concepts.
Image Captioning with Context-Aware Auxiliary Guidance
Image captioning is a challenging computer vision task, which aims to generate a natural language description of an image.
Dynamic Nonlinear Mixup with Distance-based Sample Selection
In this paper, we propose the dynamic nonlinear mixup with distance-based sample selection, which not only generates multiple sample pairs based on the distance between each sample but also enlarges the space of synthetic samples.
