robust-aggregation

Sovereign Map is a production-grade, Byzantine-tolerant Federated Learning framework. Utilizing the Mohawk Protocol for streaming aggregation, it achieves a 224x memory reduction, enabling secure orchestration of 100M+ nodes via TPM 2.0 hardware-rooted trust. Features full-stack observability with Prometheus & Grafana, built-in tokenomics telemetry

A bank-agnostic fraud-intelligence layer that learns risk thresholds across banks without any bank sharing its data — with the evaluation that says exactly how far that claim has been tested.

Offline ensemble-combiner benchmark: competence weighting and robust aggregation recover a known Bayes signal where naive averaging collapses -- a 2x2 dissociation (weighting x aggregation) plus a diversity control, numpy-only, no downloads.

Reproducible TDAW research lab for history-aware Byzantine-robust federated MNIST training, with a Rust core, Flower modes, and a Next.js dashboard.

Empirical study of the Privacy–Robustness–Performance trilemma in Federated Learning: combining DP-SGD, FLTrust Byzantine-robust aggregation, and Top-k compression across 8 configurations on MNIST, simulated with Flower.