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Sequential hypothesis testing without explicit densities is now possible with anytime-valid error control and near-optimal performance.
Independent sources can be identified even in the presence of Gaussian noise, challenging previous assumptions about the robustness of ICA models.
A unified criterion for Markov chain convergence reveals that traditional assumptions can be bypassed, streamlining the path to convergence analysis.