Federated singular value decomposition (SVD) is a foundation for many real-world
distributed applications. Existing federated SVD studies either require external servers …

Since its inception in 1982, Oja's algorithm has become an established method for
streaming principle component analysis (PCA). We study the problem of streaming PCA …

We investigate the concept of utility-preserving federated learning (UPFL) in the context of
deep neural networks. We theoretically prove and experimentally validate that UPFL …

Federated learning (FL) is emerging as a privacy-aware alternative to classical cloud-based
machine learning. In FL, the sensitive data remains in data silos and only aggregated …

Abstract We give Hoeffding-and Bernstein-type concentration inequalities for the largest
eigenvalue of sums of random matrices arising from a Markov chain. We consider time …

Block-Term Tensor Regression (BTTR) has proven to be a powerful tool for modeling
complex, high-dimensional data by leveraging multilinear relationships, making it …