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Found 4 papers, 2 papers with code
Online false discovery rate control for anomaly detection in time series
The methods proposed in this article overcome short-comings of previous FDRC rules in the context of anomaly detection, in particular ensuring that power remains high even when the alternative is exceedingly rare (typical in anomaly detection) and the test statistics are serially dependent (typical in time series).
A simple and effective predictive resource scaling heuristic for large-scale cloud applications
We propose a simple yet effective policy for the predictive auto-scaling of horizontally scalable applications running in cloud environments, where compute resources can only be added with a delay, and where the deployment throughput is limited.
FANOK: Knockoffs in Linear Time
We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large scale feature selection problems.
Error Feedback Fixes SignSGD and other Gradient Compression Schemes
These issues arise because of the biased nature of the sign compression operator.
