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11/13/2022
FedRule: Federated Rule Recommendation System with Graph Neural Networks
Much of the value that IoT (Internet-of-Things) devices bring to “smart”...
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03/17/2022
Learning Distributionally Robust Models at Scale via Composite Optimization
To train machine learning models that are robust to distribution shifts ...
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10/19/2021
Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient Distillation
Knowledge Distillation is becoming one of the primary trends among neura...
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04/04/2021
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing
As algorithmic decision-making systems are becoming more pervasive, it i...
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02/25/2021
Distributionally Robust Federated Averaging
In this paper, we study communication efficient distributed algorithms f...
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07/02/2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
In federated learning, communication cost is often a critical bottleneck...
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03/30/2020
Adaptive Personalized Federated Learning
Investigation of the degree of personalization in federated learning alg...
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11/12/2019
Efficient Fair Principal Component Analysis
The flourishing assessments of fairness measure in machine learning algo...
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10/30/2019
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Communication overhead is one of the key challenges that hinders the sca...
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11/10/2018
