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Found 6 papers, 2 papers with code
DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices
We implement DapperFL on a realworld FL platform with heterogeneous clients.
PDSR: A Privacy-Preserving Diversified Service Recommendation Method on Distributed Data
Therefore, to enable data sharing across the different platforms for diversified service recommendation, we propose a Privacy-preserving Diversified Service Recommendation (PDSR) method.
Post-Training Attribute Unlearning in Recommender Systems
The first component is distinguishability loss, where we design a distribution-based measurement to make attribute labels indistinguishable from attackers.
OptIForest: Optimal Isolation Forest for Anomaly Detection
Extensive experiments on a series of benchmarking datasets for comparative and ablation studies demonstrate that our approach can efficiently and robustly achieve better detection performance in general than the state-of-the-arts including the deep learning based methods.
Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation
It is more challenging to balance the exploration and exploitation in DRL RS where RS agent need to deeply explore the informative trajectories and exploit them efficiently in the context of recommender systems.
Diversity-aware Web APIs Recommendation with Compatibility Guarantee
Afterwards, with the diverse correlation subgraphs, we model the compatible web APIs recommendation problem to be a minimum group Steiner tree search problem.
