Search Results for author: Justin Ruths

Found 5 papers, 1 papers with code

Finite sample guarantees for quantile estimation: An application to detector threshold tuning

1 code implementation25 May 2021 David Umsonst, Justin Ruths, Henrik Sandberg

A detector threshold that provides an acceptable false alarm rate is equivalent to a specific quantile of the detector output distribution.

Anomaly Detection

Anomaly Detection Under Multiplicative Noise Model Uncertainty

no code implementations28 Mar 2021 Venkatraman Renganathan, Benjamin J. Gravell, Justin Ruths, Tyler H. Summers

State estimators are crucial components of anomaly detectors that are used to monitor cyber-physical systems.

Anomaly Detection

Performance Bounds for Neural Network Estimators: Applications in Fault Detection

no code implementations22 Mar 2021 Navid Hashemi, Mahyar Fazlyab, Justin Ruths

We exploit recent results in quantifying the robustness of neural networks to input variations to construct and tune a model-based anomaly detector, where the data-driven estimator model is provided by an autoregressive neural network.

Fault Detection

Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization

no code implementations10 Dec 2020 Navid Hashemi, Justin Ruths, Mahyar Fazlyab

Abstracting neural networks with constraints they impose on their inputs and outputs can be very useful in the analysis of neural network classifiers and to derive optimization-based algorithms for certification of stability and robustness of feedback systems involving neural networks.

Generalized Outer Bounds on the Finite Geometric Sum of Ellipsoids

no code implementations15 Jun 2020 Navid Hashemi, Justin Ruths

General results on convex bodies are reviewed and used to derive an exact closed-form parametric formula for the boundary of the geometric (Minkowski) sum of $k$ ellipsoids in $n$-dimensional Euclidean space.

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