most citedNon-Hemolytic Peptide Classification Using A Quantum Support Vector Machine

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph20243 cited

Non-Hemolytic Peptide Classification Using A Quantum Support Vector Machine

Shengxin Zhuang, John Tanner, Yusen Wu +7

Quantum machine learning (QML) is one of the most promising applications of quantum computation. However, it is still unclear whether quantum advantages exist when the data is of a…

cs.CL2023

Improving VTE Identification through Adaptive NLP Model Selection and Clinical Expert Rule-based Classifier from Radiology Reports

Jamie Deng, Yusen Wu, Hilary Hayssen +8

Rapid and accurate identification of Venous thromboembolism (VTE), a severe cardiovascular condition including deep vein thrombosis (DVT) and pulmonary embolism (PE), is important…

quant-ph20231 cited

Trainability Analysis of Quantum Optimization Algorithms from a Bayesian Lens

Yanqi Song, Yusen Wu, Sujuan Qin +3

The Quantum Approximate Optimization Algorithm (QAOA) is an extensively studied variational quantum algorithm utilized for solving optimization problems on near-term quantum device…

cs.CR2023

Enabling Quartile-based Estimated-Mean Gradient Aggregation As Baseline for Federated Image Classifications

Yusen Wu, Jamie Deng, Hao Chen +2

Federated Learning (FL) has revolutionized how we train deep neural networks by enabling decentralized collaboration while safeguarding sensitive data and improving model performan…

cs.LG20231 cited

Soft Merging: A Flexible and Robust Soft Model Merging Approach for Enhanced Neural Network Performance

Hao Chen, Yusen Wu, Phuong Nguyen +2

Stochastic Gradient Descent (SGD), a widely used optimization algorithm in deep learning, is often limited to converging to local optima due to the non-convex nature of the problem…