3 papers
cs.CR2024
Measuring Privacy Loss in Distributed Spatio-Temporal Data
Tatsuki Koga, Casey Meehan, Kamalika Chaudhuri
Statistics about traffic flow and people's movement gathered from multiple geographical locations in a distributed manner are the driving force powering many applications, such as…
cs.LG2023
Differentially Private Multi-Site Treatment Effect Estimation
Tatsuki Koga, Kamalika Chaudhuri, David Page
Patient privacy is a major barrier to healthcare AI. For confidentiality reasons, most patient data remains in silo in separate hospitals, preventing the design of data-driven heal…
cs.LG2023
Population Expansion for Training Language Models with Private Federated Learning
Tatsuki Koga, Congzheng Song, Martin Pelikan +1
Federated learning (FL) combined with differential privacy (DP) offers machine learning (ML) training with distributed devices and with a formal privacy guarantee. With a large pop…