Search Results for author:
Found 9 papers, 3 papers with code
M3BAT: Unsupervised Domain Adaptation for Multimodal Mobile Sensing with Multi-Branch Adversarial Training
Moreover, we proposed a novel improvement over DANN, called M3BAT, unsupervised domain adaptation for multimodal mobile sensing with multi-branch adversarial training, to account for the multimodality of sensor data during domain adaptation with multiple branches.
Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework
This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement.
Framing the News:From Human Perception to Large Language Model Inferences
Identifying the frames of news is important to understand the articles' vision, intention, message to be conveyed, and which aspects of the news are emphasized.
ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees
Graph Neural Networks (GNNs) have become a popular tool for learning on graphs, but their widespread use raises privacy concerns as graph data can contain personal or sensitive information.
Your Day in Your Pocket: Complex Activity Recognition from Smartphone Accelerometers
Human Activity Recognition (HAR) enables context-aware user experiences where mobile apps can alter content and interactions depending on user activities.
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation
In this paper, we study the problem of learning Graph Neural Networks (GNNs) with Differential Privacy (DP).
Smartphone Sensing for the Well-being of Young Adults: A Review
Over the years, mobile phones have become versatile devices with a multitude of capabilities due to the plethora of embedded sensors that enable them to capture rich data unobtrusively.
Human-Computer Interaction
Locally Private Graph Neural Networks
In this paper, we study the problem of node data privacy, where graph nodes have potentially sensitive data that is kept private, but they could be beneficial for a central server for training a GNN over the graph.
Words Worth: Verbal Content and Hirability Impressions in YouTube Video Resumes
Automatic hirability prediction from video resumes is gaining increasing attention in both psychology and computing.
