Papers by Zhenhou Hong

1 papers
Empirical Studies of Institutional Federated Learning For Natural Language Processing (2020.findings-emnlp)

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Challenge: federated learning is a promising ideology to unite isolated datasets for machine learning problems.
Approach: They propose to use federated natural language processing networks to train a popular NLP model with applications in sentence intent classification.
Outcome: The proposed model is sensitive to imbalanced data load and tested against a federated model under imbalanced datasets.

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