The Federated and Distributed Machine Learning Conference

As federated learning expands and more institutions and companies begin to explore the capabilities of this model, there's a quickly growing need for an event which can highlight the very latest developments in this growing area. The Federated Learning Conference is being organized to provide a dynamic learning environment for both academic and industry leaders to facilitate the growth of federated learning and establish the networks that will be vital to its development and promulgation.

Federated learning is a distributed machine learning system which enables model training on a large body of decentralized data. Federated learning aims to make industries effectively and accurately use data across organizations while meeting regulatory, privacy, and security requirements. Unlike traditional machine learning, federated learning brings the model to the data.

Below is a partial list of our speakers for this event.

Speakers: Akshay Sharma, Chief Technology Officer, Doc.AI, Marcin Rojek, Co-Founder, ByteLake, Ramesh Raskar, Associate Professor of Computer Science, MIT, Anila Joshi, Machine Learning/AI Technical Leader, Global AI Accelerator, Ericsson, NIrmit Desai, Ph.D., Research Staff Member And Manager, Edge Computing, IBM Research

Others Details

Time: 8:30 am to 2:40 pm