Abstract: In federated learning, non-independently and non-identically distributed heterogeneous data on the clients can limit both the convergence speed and model utility of federated learning, and ...
Abstract: The need for data protection in national critical information infrastructure units has become more and more urgent with the deepening of digital transformation. At present, the rapid ...
Low-rank data analysis has emerged as a powerful paradigm across applied mathematics, statistics, and data science. With the rapid growth of modern datasets in size, dimensionality, and complexity, ...
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