Bayesian Error-in-Variables Models for the Identification of Distribution Grids

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Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

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We consider multi-agent networks that aim at solving, cooperatively and online, distributed optimization problems under communication constraints. We propose the ACTC (Adapt-Compress-Then-Combine) diffusion strategy, which leverages differential randomized ...

Bayesian Error-in-Variables Models for the Identification of Distribution Grids

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An Exponentially Converging Particle Method for the Mixed Nash Equilibrium of Continuous Games

Contact Tip Trajectory in Steady-State Regime Prediction Using Deep Learning for Piezoelectric Actuators

Decentralized coordination between active distribution network and multi-microgrids through a fast decentralized adjustable robust operation framework

Machine Learning Security in Industry: A Quantitative Survey

Microstructure formation in micron-scale thin-walled Hastelloy X samples fabricated with laser powder bed fusion

Validating Automatic Speech Recognition and Understanding for Pre-Filling Radar Labels-Increasing Safety While Reducing Air Traffic Controllers' Workload

Bimanual dynamic grabbing and tossing of objects onto a moving target

Raising the temperature on electrodes for anion exchange membrane electrolysis-activity and stability aspects

Sparse Attacks for Manipulating Explanations in Deep Neural Network Models

Partial Information Sharing Over Social Learning Networks

Extended Temperature Modeling of InGaAs/InP SPADs

Privacy-Preserving Image Acquisition for Neural Vision Systems

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

Adaptive Diffusion With Compressed Communication