10 papers
Federated Generation of Synthetic RNA-seq Data
Daniil Filienko, Martine De Cock, Sikha Pentyala
Access to genomic data is highly regulated due to its sensitive nature. While safeguards are essential, cumbersome data access processes pose a significant barrier to the developme…
End to End Collaborative Synthetic Data Generation
Sikha Pentyala, Geetha Sitaraman, Trae Claar +1
The success of AI is based on the availability of data to train models. While in some cases a single data custodian may have sufficient data to enable AI, often multiple custodians…
FHAIM: Fully Homomorphic AIM For Private Synthetic Data Generation
Mayank Kumar, Qian Lou, Paulo Barreto +2
Data is the lifeblood of AI, yet much of the most valuable data remains locked in silos due to privacy and regulations. As a result, AI remains heavily underutilized in many of the…
Large Language Model-Powered Conversational Agent Delivering Problem-Solving Therapy (PST) for Family Caregivers: Enhancing Empathy and Therapeutic Alliance Using In-Context Learning
Liying Wang, Ph. D., Daffodil Carrington +8
Family caregivers often face substantial mental health challenges due to their multifaceted roles and limited resources. This study explored the potential of a large language model…
Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy
Khaoula Chehbouni, Martine De Cock, Gilles Caporossi +3
The increased screen time and isolation caused by the COVID-19 pandemic have led to a significant surge in cases of online grooming, which is the use of strategies by predators to…
Privacy Vulnerabilities in Marginals-based Synthetic Data
Steven Golob, Sikha Pentyala, Anuar Maratkhan +1
When acting as a privacy-enhancing technology, synthetic data generation (SDG) aims to maintain a resemblance to the real data while excluding personally-identifiable information.…