FL-Sailer combines adaptive leverage score sampling and an invariant VAE in a federated setup to enable privacy-preserving analysis of high-dimensional sparse scATAC-seq data, with a convergence bound and reported outperformance of centralized baselines.
The separation after sampling ˜∆ ij satisfies: P [ (1−2ϵ)∆ ij≤˜∆ ij≤(1 + 2ϵ)∆ ij ] ≥1−δ
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FL-Sailer: Efficient and Privacy-Preserving Federated Learning for Scalable Single-Cell Epigenetic Data Analysis via Adaptive Sampling
FL-Sailer combines adaptive leverage score sampling and an invariant VAE in a federated setup to enable privacy-preserving analysis of high-dimensional sparse scATAC-seq data, with a convergence bound and reported outperformance of centralized baselines.