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05/15/2023
Federated Learning over Harmonized Data Silos
Federated Learning is a distributed machine learning approach that enabl...
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05/02/2022
Performance Weighting for Robust Federated Learning Against Corrupted Sources
Federated Learning has emerged as a dominant computational paradigm for ...
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03/28/2022
Federated Named Entity Recognition
We present an analysis of the performance of Federated Learning in a par...
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12/10/2021
Building Autocorrelation-Aware Representations for Fine-Scale Spatiotemporal Prediction
Many scientific prediction problems have spatiotemporal data- and modeli...
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08/07/2021
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
Federated learning (FL) enables distributed computation of machine learn...
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05/06/2021
Membership Inference Attacks on Deep Regression Models for Neuroimaging
Ensuring the privacy of research participants is vital, even more so in ...
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02/16/2021
Scaling Neuroscience Research using Federated Learning
The amount of biomedical data continues to grow rapidly. However, the ab...
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02/04/2021
Semi-Synchronous Federated Learning
There are situations where data relevant to a machine learning problem a...
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08/25/2020
Accelerating Federated Learning in Heterogeneous Data and Computational Environments
There are situations where data relevant to a machine learning problem a...
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06/01/2019
Biomedical Named Entity Recognition via Reference-Set Augmented Bootstrapping
We present a weakly-supervised data augmentation approach to improve Nam...
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11/19/2018
NSEEN: Neural Semantic Embedding for Entity Normalization
Much of human knowledge is encoded in the text, such as scientific publi...
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01/16/2016
Learning the Semantics of Structured Data Sources
Information sources such as relational databases, spreadsheets, XML, JSO...
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09/09/2009
