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01/08/2021
Differentially Private Federated Learning for Cancer Prediction
Since 2014, the NIH funded iDASH (integrating Data for Analysis, Anonymi...
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08/17/2020
Siloed Federated Learning for Multi-Centric Histopathology Datasets
While federated learning is a promising approach for training deep learn...
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07/29/2020
SAFER: Sparse secure Aggregation for FEderated leaRning
Federated learning enables one to train a common machine learning model ...
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12/12/2019
Efficient Per-Example Gradient Computations in Convolutional Neural Networks
Deep learning frameworks leverage GPUs to perform massively-parallel com...
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06/12/2018
ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors
Timely assessment of compound toxicity is one of the biggest challenges ...
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02/01/2018
Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach
Analysis of histopathology slides is a critical step for many diagnoses,...
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12/21/2017
Robust Detection of Covariate-Treatment Interactions in Clinical Trials
Detection of interactions between treatment effects and patient descript...
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06/02/2017
Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing
In statistical learning for real-world large-scale data problems, one mu...
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02/10/2017
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines
Restricted Boltzmann machines (RBMs) are energy-based neural-networks wh...
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06/13/2016
Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines
In this work, we consider compressed sensing reconstruction from M measu...
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10/05/2015
Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach
In this paper, the problem of compressive imaging is addressed using nat...
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06/09/2015
Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy
Restricted Boltzmann machines are undirected neural networks which have ...
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02/23/2015
Approximate Message Passing with Restricted Boltzmann Machine Priors
Approximate Message Passing (AMP) has been shown to be an excellent stat...
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09/19/2014