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Protecting ML classifiers from adversarial examples is crucial. We propose that the main threat is an attacker perturbing a confidently classified input to produce a confident misclassification. We consider in this paper the attack in which a small number ...
Security system designers favor worst-case security metrics, such as those derived from differential privacy (DP), due to the strong guarantees they provide. On the downside, these guarantees result in a high penalty on the system's performance. In this pa ...
IEEE2023
We develop an exchange rate target zone model with finite exit time and non-Gaussian tails. We show how the tails are a consequence of time-varying investor risk aversion, which generates mean-preserving spreads in the fundamental distribution. We solve ex ...
Lay Summary The aim of this study is to determine whether using polygenic risk scores improves the prediction of atherosclerotic cardiovascular disease risk when combined with clinical scores currently recommended by European and US guidelines on cardiovas ...
This paper presents quantitative information on the effectiveness of seismic retrofit solutions using bilinear oil dampers for seismically deficient existing tall steel buildings. For this purpose, a benchmark 40-story steel space moment-resisting frame bu ...
Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...
The detection of digital face manipulation in video has attracted extensive attention due to the increased risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been developed and ha ...
Uncertainty of spillover effects – including property devaluation - from proposed land-use change elicits opposition to local development. This hinders cities’ ability to implement land-use policy aimed at housing affordability and environmental sustainabi ...
Central banks are increasingly concerned about climate-related risks and want to ensure that the financial system is resilient to them. As they integrate these risks into financial stability monitoring, they also discuss how to apply environmental criteria ...
With the overall goal of reducing the numerical burden of uncertainty quantification involved in seismic risk assessments, this paper examines opportunities for assessment of seismic collapse capacity and risk using data-driven surrogates as a complement t ...