A qualitative AI security risk assessment of autonomous vehicles

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To protect both local gradients and estimated parameters in distributed learning, this paper introduces a masked diffusion (MD) strategy, leading to two algorithms: the MD stochastic gradient (MD-SG) and the MD primal-dual stochastic gradient (MPD-SG). The ...

We propose a machine learning-based estimator of the hand state for rehabilitation purposes, using light exoskeletons. These devices are easy to use and useful for delivering domestic and frequent therapies. We build a supervised approach using information ...

A first-principles approach for calculating ion separation in solution through two-dimensional (2D) membranes is proposed and applied. Ionic energy profiles across the membrane are obtained first, where solvation effects are simulated explicitly with machi ...

Virtual reality (VR) technology revitalises rehabilitation training by creating rich, interactive virtual rehabilitation scenes and tasks that deeply engage patients. Robotics with immersive VR environments have the potential to significantly enhance the s ...

With the rise of open data, identifiability of individuals based on 3D renderings obtained from routine structural magnetic resonance imaging (MRI) scans of the head has become a growing privacy concern. To protect subject privacy, several algorithms have ...

Electrochemical devices and systems are significant for the development of therapeutic drug monitoring (TDM) and personalized therapy. However, electrochemical sensors are usually not that much selective. Therefore, innovative machine learning (ML) approac ...

There are two main attack models considered in the adversarial robustness literature: black-box and white-box. We consider these threat models as two ends of a fine-grained spectrum, indexed by the number of queries the adversary can ask. Using this point ...

We investigate how the training curve of isotropic kernel methods depends on the symmetry of the task to be learned, in several settings. (i) We consider a regression task, where the target function is a Gaussian random field that depends only on d(paralle ...

Human-object interaction is of great relevance for robots to operate in human environments. However, state-of-the-art robotic hands are far from replicating humans skills. It is, therefore, essential to study how humans use their hands to develop similar r ...

A qualitative AI security risk assessment of autonomous vehicles

Chat with Graph Search

Masked Diffusion Strategy for Privacy-Preserving Distributed Learning

Learning Hand State Estimation for a Light Exoskeleton

Ion Sieving in Two-Dimensional Membranes from First Principles

Rehabilitation exoskeleton system with bidirectional virtual reality feedback training strategy

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency

Simultaneous Quantification of Multiple Drugs by Machine Learning on Electrochemical Sensors

Query Complexity of Adversarial Attacks

How isotropic kernels perform on simple invariants

Hand-Object Interaction: From Human Demonstrations to Robot Manipulation