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Matrix-factorized private streams and optimized correlated-noise training

Contribution grade

Private streaming and optimization · Human-designed research method or resource

Reference score125,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Recast continual-release private sums and momentum schedules as matrix mechanisms, analyzing Gaussian privacy under adaptive inputs and computing error-efficient factorizations with a fixed-point method.

Scientific scope

Recast continual-release private sums and momentum schedules as matrix mechanisms, analyzing Gaussian privacy under adaptive inputs and computing error-efficient factorizations with a fixed-point method. Original v1 has three authors; expanded v3 has five, adds adaptive-stream theory/application and a different title. Gaussian adaptive transfer requires a lower-triangular full-rank query and bounded transformed neighboring-stream sensitivity; not arbitrary noise. Factorization error optimality is within the stated mechanism/error class. Fixed-point convergence is proved locally while global behavior is numerical; single-pass adjacency cannot silently cover unrestricted repeated user participation.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Original v1 has three authors; expanded v3 has five, adds adaptive-stream theory/application and a different title. Gaussian adaptive transfer requires a lower-triangular full-rank query and bounded transformed neighboring-stream sensitivity; not arbitrary noise. Factorization error optimality is within the stated mechanism/error class. Fixed-point convergence is proved locally while global behavior is numerical; single-pass adjacency cannot silently cover unrestricted repeated user participation.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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