Adaptive Information-Sharing for Privacy-Aware Mobile Social Networks

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The conceptual design phase is a fascinating moment to observe how a design task is interpreted, as the (often implicit) relative importance students accord to the various requirements and constraints offers a window into the thinking underpinning their de ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

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The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

Adaptive Information-Sharing for Privacy-Aware Mobile Social Networks

Chat with Graph Search

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On the (In)security of Peer-to-Peer Decentralized Machine Learning

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Not Yet Another Digital ID: Privacy-Preserving Humanitarian Aid Distribution

Efficient and Accurate Peer-to-Peer Training of Machine Learning Based Home Thermal Models

P3LI5: Practical and confidEntial Lawful Interception on the 5G core

Methodology for selecting measurement points that optimize information gain for model updating

Spatial-Temporal Graph Attention Fuser for Calibration in IoT Air Pollution Monitoring Systems

Framework to evaluate the value of monitoring-technique information for structural performance monitoring

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Regularization Techniques for Low-Resource Machine Translation

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

Curiosity-driven exploration: foundations in neuroscience and computational modeling

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision