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(video) Efficient and privacy friendly decentralized learning with an automotive perspective, Dr Jan Ramon

Workshop: Collaborative Perception & Federated ML for Autonomous Driving

Speaker : Dr. Jan Ramon

Abstract : Modern cars can generate more data worth analyzing than can be affordably transported by a classic 4G network. There is an increasing need for intelligent strategies to process and analyze data, and as each has some drawbacks probably a combination of strategies will be needed in the future.

In this presentation, I’ll discuss decentralized learning, with special attention for the automotive setting. Among others, I’ll argue decentralized learning allows for improved privacy-friendliness and improved efficiency. I’ll also discuss a number of limitations, where restricted forms of coordination can be useful.

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