91 citations · 223 across the 30 of their papers we have counts for
9 papers · 1 filter
ATOM: An Efficient Topology Adaptive Algorithm for Minor Embedding in Quantum Computing
Hoang M. Ngo, Tamer Kahveci, My T. Thai
Quantum annealing (QA) has emerged as a powerful technique to solve optimization problems by taking advantages of quantum physics. In QA process, a bottleneck that may prevent QA t…
When Decentralized Optimization Meets Federated Learning
Hongchang Gao, My T. Thai, Jie Wu
Federated learning is a new learning paradigm for extracting knowledge from distributed data. Due to its favorable properties in preserving privacy and saving communication costs,…
Deep Graph Representation Learning and Optimization for Influence Maximization
Chen Ling, Junji Jiang, Junxiang Wang +5
Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users. Researchers have made great…
Linear Query Approximation Algorithms for Non-monotone Submodular Maximization under Knapsack Constraint
Canh V. Pham, Tan D. Tran, Dung T. K. Ha +1
This work, for the first time, introduces two constant factor approximation algorithms with linear query complexity for non-monotone submodular maximization over a ground set of si…
Cultural-aware Machine Learning based Analysis of COVID-19 Vaccine Hesitancy
Raed Alharbi, Sylvia Chan-Olmsted, Huan Chen +1
Understanding the COVID-19 vaccine hesitancy, such as who and why, is very crucial since a large-scale vaccine adoption remains as one of the most efficient methods of controlling…
LAVA: Granular Neuron-Level Explainable AI for Alzheimer's Disease Assessment from Fundus Images
Nooshin Yousefzadeh, Charlie Tran, Adolfo Ramirez-Zamora +3
Alzheimer's Disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia. Early diagnosis is critical for patients to benefit from potential interventi…