research
∙
09/11/2023
Towards Federated Learning Under Resource Constraints via Layer-wise Training and Depth Dropout
Large machine learning models trained on diverse data have recently seen...
share
research
∙
05/23/2023
Federated Variational Inference: Towards Improved Personalization and Generalization
Conventional federated learning algorithms train a single global model b...
research
∙
12/26/2022
Large Language Models Encode Clinical Knowledge
Large language models (LLMs) have demonstrated impressive capabilities i...
research
∙
09/30/2022
Federated Training of Dual Encoding Models on Small Non-IID Client Datasets
Dual encoding models that encode a pair of inputs are widely used for re...
research
∙
05/26/2022
Mixed Federated Learning: Joint Decentralized and Centralized Learning
Federated learning (FL) enables learning from decentralized privacy-sens...
research
∙
10/27/2021
What Do We Mean by Generalization in Federated Learning?
Federated learning data is drawn from a distribution of distributions: c...
research
∙
08/18/2021
Learning Federated Representations and Recommendations with Limited Negatives
Deep retrieval models are widely used for learning entity representation...
research
∙
02/05/2021
Federated Reconstruction: Partially Local Federated Learning
Personalization methods in federated learning aim to balance the benefit...
research
∙
05/29/2019