Now showing items 11-16 of 16
A Deep Learning Approach for Generating Soft Range Information from RF Data
Radio frequency (RF)-based techniques are widely adopted for indoor localization despite the challenges in extracting sufficient information from measurements. Soft range information (SRI) offers a promising alternative ...
Derivation of a Cost-Sensitive COVID-19 Mortality Risk Indicator Using a Multistart Framework
The overall global death rate for COVID-19 patients has escalated to 2.13% after more than a year of worldwide spread. Despite strong research on the infection pathogenesis, the molecular mechanisms involved in a fatal ...
A Multivariate Time Series Streaming Classifier for Predicting Hard Drive Failures [Application Notes]
Digital data storage systems such as hard drives can suffer breakdowns that cause the loss of stored data. Due to the cost of data and the damage that its loss entails, hard drive failure prediction is vital. In this ...
Analysis of Dominant Classes in Universal Adversarial Perturbations
The reasons why Deep Neural Networks are susceptible to being fooled by adversarial examples remains an open discussion. Indeed, many differ- ent strategies can be employed to efficiently generate adversarial attacks, some ...
Rank aggregation for non-stationary data streams
The problem of learning over non-stationary ranking streams arises naturally, particularly in recommender systems. The rankings represent the preferences of a population, and the non-stationarity means that the distribution ...
Ad-Hoc Explanation for Time Series Classification
In this work, a perturbation-based model-agnostic explanation method for time series classification is presented. One of the main novelties of the proposed method is that the considered perturbations are interpretable and ...