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05/24/2023
READ: Recurrent Adaptation of Large Transformers
Fine-tuning large-scale Transformers has led to the explosion of many AI...
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05/05/2023
Now It Sounds Like You: Learning Personalized Vocabulary On Device
In recent years, Federated Learning (FL) has shown significant advanceme...
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10/14/2022
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning
An oft-cited challenge of federated learning is the presence of heteroge...
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06/30/2022
Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning
An oft-cited challenge of federated learning is the presence of data het...
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05/30/2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity
Federated learning (FL) is an effective mechanism for data privacy in re...
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11/08/2021
Papaya: Practical, Private, and Scalable Federated Learning
Cross-device Federated Learning (FL) is a distributed learning paradigm ...
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09/25/2021
Opacus: User-Friendly Differential Privacy Library in PyTorch
We introduce Opacus, a free, open-source PyTorch library for training de...
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06/11/2021
Federated Learning with Buffered Asynchronous Aggregation
Federated Learning (FL) trains a shared model across distributed devices...
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07/02/2020
