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Found 7 papers, 0 papers with code
A Dual Stealthy Backdoor: From Both Spatial and Frequency Perspectives
Then, to attain strong stealthiness, we incorporate Fourier Transform and Discrete Cosine Transform to mix the poisoned image and clean image in the frequency domain.
Balancing Privacy Protection and Interpretability in Federated Learning
Federated learning (FL) aims to collaboratively train the global model in a distributed manner by sharing the model parameters from local clients to a central server, thereby potentially protecting users' private information.
Adversarial RAW: Image-Scaling Attack Against Imaging Pipeline
Most of the vision devices are equipped with image signal processing (ISP) pipeline to implement RAW-to-RGB transformations and embedded into data preprocessing module for efficient image processing.
Heterogeneous Graph Learning for Explainable Recommendation over Academic Networks
We devise an unsupervised learning model called HAI (Heterogeneous graph Attention InfoMax) which aggregates attention mechanism and mutual information for institution recommendation.
MSCET: A Multi-Scenario Offloading Schedule for Biomedical Data Processing and Analysis in Cloud-Edge-Terminal Collaborative Vehicular Networks
The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge.
VRConvMF: Visual Recurrent Convolutional Matrix Factorization for Movie Recommendation
Fortunately, context-aware recommender systems can alleviate the sparsity problem by making use of some auxiliary information, such as the information of both the users and items.
Edge Data Based Trailer Inception Probabilistic Matrix Factorization for Context-Aware Movie Recommendation
As an effective way to alleviate information overload, recommender system can improve the quality of various services by adding application data generated by users on edge devices, such as visual and textual information, on the basis of sparse rating data.
