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Horizontal Federated Learning with Intel® Trust Domain Extensions (Intel® TDX) on VMware® ESXi
June 6, 3:45 PM - 4:05 PM
Imperial Room A
Intel® Trust Domain Extensions (Intel® TDX) is designed to isolate Trust Domain (TD) VMs from the hypervisor and other non-TD software on the host platform to enhance confidential computing from broad range of software attacks. Federated Learning is a machine learning algorithm that allows a model to be trained across multiple decentralized nodes without explicitly exchanging local data samples. In this session, we describe the use case of running Federated Learning to train a global machine learning model collaboratively across a network of trust domains running on VMware® ESXi while keeping the sensitive data localized.
About the speakers
Kuo-Lang Tseng
Software Engineer, Intel Corporation
Software development and technical lead.
Sanrio Alvares
Software Engineer, Intel Corporation
Sanrio is a Software Engineer with experience in system software engineering, particularly focused on Kernel/BIOS software. His role covers all aspects of software development, spanning the addition of new features, debugging problems, and fine-tuning code for better performance. His interests outside of work are varied and include but are not limited to playing music, soccer, and keeping his BMI in check.