1 citations · 1 across the 3 of their papers we have counts for
5 papers
ReLEAF: A Socio-Technical Framework Bridging Custodians and Researchers for Trustworthy Data Sharing
Hibiki Ito, Chia-Yu Hsu, Hiroaki Ogata
Growing volumes of educational real-world data (ERWD) are being collected across learning platforms and institutional systems. Sharing these data within the Learning Analytics comm…
Training-Free Private Synthesis with Validation: A New Frontier for Practical Educational Data Sharing
Hibiki Ito, Chia-Yu Hsu, Hiroaki Ogata
While secondary use of real-world data (RWD) in education offers substantial research opportunities, data sharing is often limited by privacy constraints. Differentially private sy…
Cyclic Adaptive Private Synthesis for Sharing Real-World Data in Education
Hibiki Ito, Chia-Yu Hsu, Hiroaki Ogata
The rapid adoption of digital technologies has greatly increased the volume of real-world data (RWD) in education. While these data offer significant opportunities for advancing le…
The Third-Party Access Effect: An Overlooked Challenge in Secondary Use of Educational Real-World Data
Hibiki Ito, Chia-Yu Hsu, Hiroaki Ogata
Secondary use of growing real-world data (RWD) in education offers significant opportunities for research, yet privacy practices intended to enable third-party access to such RWD a…
Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning
Marlon Tobaben, Hibiki Ito, Joonas Jälkö +2
Membership inference attacks (MIAs) are used to test practical privacy of machine learning models. MIAs complement formal guarantees from differential privacy (DP) under a more rea…