News & features
FLUTE: A scalable federated learning simulation platform
| Dimitrios Dimitriadis, Mirian Hipolito Garcia, Daniel Eduardo Madrigal Diaz, Andre Manoel, and Robert Sim
Federated learning has become a major area of machine learning (ML) research in recent years due to its versatility in training complex models over massive amounts of data without the need to share that data with a centralized entity. However,…
Privacy Preserving Machine Learning: Maintaining confidentiality and preserving trust
| Victor Ruehle, Robert Sim, Sergey Yekhanin, Nishanth Chandran, Melissa Chase, Daniel Jones, Kim Laine, Boris Köpf, Jaime Teevan, Jim Kleewein, and Saravan Rajmohan
Machine learning (ML) offers tremendous opportunities to increase productivity. However, ML systems are only as good as the quality of the data that informs the training of ML models. And training ML models requires a significant amount of data, more…