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FLINT: A Platform for Federated Learning Integration
Cross-device federated learning (FL) has been well-studied from algorithmic, system scalability, and training speed perspectives.
Block-wise Partitioning for Extreme Multi-label Classification
Extreme multi-label classification aims to learn a classifier that annotates an instance with a relevant subset of labels from an extremely large label set.
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