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Online Multi-Kernel Learning with Graph-Structured Feedback
The selection of the dictionary has crucial impact on both the performance and complexity of MKL.
Graph-Assisted Communication-Efficient Ensemble Federated Learning
At each learning round, the server selects a subset of pre-trained models to construct the ensemble model based on the structure of a graph, which characterizes the server's confidence in the models.
Online Learning with Uncertain Feedback Graphs
In this context, the relationship among experts can be captured by a feedback graph, which can be used to assist the learner's decision making.
Graph-Aided Online Multi-Kernel Learning
To improve the accuracy of function approximation and reduce the computational complexity, the present paper studies data-driven selection of kernels from the dictionary that provide satisfactory function approximations.
