Shekar Ramachandran, currently working as a Senior Member Technical Staff at Intel Corporation aims at scaling heights of success by leaving marks of excellence. He believes in setting high goals and pushing himself toward achieving them. A result-oriented and performance-driven professional with an experience of nearly 21 years in the IT industry, Shekar has hands-on experience in the embedded & mobile domain. He has rich experience in working in the IOTG domain on vision portfolio, working on AI & ML, technically managing staff, monitoring system requirements, resolving technical issues, debugging, showcasing financial & business expertise, performing system integration, and integrating complex systems. An out-of-the-box thinker with strong interpersonal, organizational, management, communication, and relationship-building skills he possesses strong business acumen and the capability to convert visuals into reality.
Shekar Ramachandran
Senior Member Technical Staff at Intel
All Sessions by Shekar Ramachandran
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Day 2
Jan 20, 2023
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11:15
<i>[Paper Presentation]</i> EthicalFL - An Optimized Federated Learning Framework with Bias Mitigation
11:15 - 11:35Federated learning helps one leverage AI/ML techniques while preserving the privacy of localized data. However, owing to its decentralized nature, Federated Learning faces several optimization issues. This paper identifies the problem of incoming network congestion concerning the Aggregator in a federated scenario and proposes a statistical significance test to address the problem. Further network optimization is done by implementing a requirement-based request-response communication architecture to reduce unnecessary training rounds. This research also targets the infamous bias problem introduced due to label bias at the clients in a cross-device FL setting. The proposed solution defines a novel biasing factor to tackle data bias in the Aggregated model per the principles of AI ethics without violating privacy norms.Audi 3
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