research
∙
09/15/2023
A new method of modeling the multi-stage decision-making process of CRT using machine learning with uncertainty quantification
Aims. The purpose of this study is to create a multi-stage machine learn...
share
research
∙
06/02/2023
A new method using deep transfer learning on ECG to predict the response to cardiac resynchronization therapy
Background: Cardiac resynchronization therapy (CRT) has emerged as an ef...
research
∙
05/04/2023
A new method using deep learning to predict the response to cardiac resynchronization therapy
Background. Clinical parameters measured from gated single-photon emissi...
research
∙
04/21/2023
Persistently Trained, Diffusion-assisted Energy-based Models
Maximum likelihood (ML) learning for energy-based models (EBMs) is chall...
research
∙
03/16/2023
GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data
Vertical federated learning (VFL) is a distributed learning paradigm, wh...
research
∙
11/06/2022
Enabling Deep Learning-based Physical-layer Secret Key Generation for FDD-OFDM Systems in Multi-Environments
Deep learning-based physical-layer secret key generation (PKG) has been ...
research
∙
07/17/2022
Automatic Context Pattern Generation for Entity Set Expansion
Entity Set Expansion (ESE) is a valuable task that aims to find entities...
research
∙
04/27/2022
Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective
Distributed algorithms have been playing an increasingly important role ...
research
∙
06/25/2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy
Providing privacy protection has been one of the primary motivations of ...
research
∙
06/01/2021
A method using deep learning to discover new predictors of CRT response from mechanical dyssynchrony on gated SPECT MPI
Background. Studies have shown that the conventional left ventricular me...
research
∙
05/18/2021
Deep Learning-based Physical-Layer Secret Key Generation for FDD Systems
Physical-layer key generation (PKG) establishes cryptographic keys from ...
research
∙
12/22/2020
Hybrid Federated Learning: Algorithms and Implementation
Federated learning (FL) is a recently proposed distributed machine learn...
research
∙
06/15/2020
Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
prevention of stroke with its associated risk factors has been one of th...
research
∙
05/22/2020
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data
Federated Learning (FL) has become a popular paradigm for learning from ...
research
∙
05/17/2020
On loss functions and regret bounds for multi-category classification
We develop new approaches in multi-class settings for constructing prope...
research
∙
01/14/2020
Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond
Distributed learning has become a critical enabler of the massively conn...
research
∙
12/24/2019
A Communication Efficient Vertical Federated Learning Framework
One critical challenge for applying today's Artificial Intelligence (AI)...
research
∙
06/19/2019
