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Hochschule Karlsruhe Hochschule Karlsruhe - University of Applied Sciences Hochschule Karlsruhe Hochschule Karlsruhe - University of Applied Sciences
Hochschule Karlsruhe Hochschule Karlsruhe - University of Applied Sciences

Publication on Machine Learning and Privacy at IPCCC 2024

At the IEEE IPCCC 2024 in Orlando, Florida, David Monschein showcased research on efficient and secure machine learning using homomorphic encryption. His presentation highlighted the HEJet framework, which enhances privacy-preserving neural network computations while improving inference efficiency.
David Monschein presenting 'HEJet: A Framework for Efficient Machine Learning Inference with Homomorphic Encryption' at IPCCC 2024.

From November 22-24, 2024, David Monschein from Institute of Data-Centric Software Systems participated in the 43rd IEEE International Performance, Computing, and Communications Conference (IPCCC 2024) in Orlando, Florida. The event gathered researchers and professionals to discuss innovations in computing and communication.

David Monschein presented the paper "HEJet: A Framework for Efficient Machine Learning Inference with Homomorphic Encryption," which addresses the challenge of performing secure computations on encrypted data while maintaining efficiency and accuracy. HEJet streamlines the application of neural networks with homomorphic encryption by optimizing numerical computations, achieving notable speed improvements over existing methods.

The conference provided a platform for engaging discussions with experts, fostering knowledge exchange and potential collaborations in privacy-preserving machine learning. Through participation in presentations and networking sessions, David Monschein contributed to advancing research and strengthening Institute of Data-Centric Software Systems’s presence in the field.

IPCCC 2024 featured keynote talks, panel discussions, and interactive sessions, offering valuable insights and connections for all attendees. The event highlighted ongoing developments in secure computing and reinforced the importance of research in privacy-preserving technologies.