Rick Siow Mong Goh
4 papers in the PaperMetrix corpus
Papers by this author
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Dual Adversarial Neural Transfer for Low-Resource Named Entity Recognition
2019
We propose a new neural transfer method termed Dual Adversarial Transfer Network (DATNet) for addressing low-resource Named Entity Recognition (NER). Specifically, two variants of DATNet, i.e., DATNet-F and DATNet-P, are investigated to explore effective feature …
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CE-Fed: Communication efficient multi-party computation enabled federated learning
2022 · Array
Federated learning (FL) allows a number of parties collectively train models without revealing private datasets. There is a possibility of extracting personal or confidential data from the shared models even-though sharing of raw data is …
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Reliable Federated Disentangling Network for Non-IID Domain Feature
2023 · arXiv (Cornell University)
Federated learning (FL), as an effective decentralized distributed learning approach, enables multiple institutions to jointly train a model without sharing their local data. However, the domain feature shift caused by different acquisition devices/clients substantially degrades …
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An Aggregation-Free Federated Learning for Tackling Data Heterogeneity
2024 · arXiv (Cornell University)
The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where clients update local models based on a global model aggregated by …