9 citations · 25 across the 6 of their papers we have counts for
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cs.LG2023★ 2 cited
A Corrected Expected Improvement Acquisition Function Under Noisy Observations
Han Zhou, Xingchen Ma, Matthew B Blaschko
Sequential maximization of expected improvement (EI) is one of the most widely used policies in Bayesian optimization because of its simplicity and ability to handle noisy observat…
eess.IV2023★ 9 cited
Inverse Lithography Physics-informed Deep Neural Level Set for Mask Optimization
Xing-Yu Ma, Shaogang Hao
As the feature size of integrated circuits continues to decrease, optical proximity correction (OPC) has emerged as a crucial resolution enhancement technology for ensuring high pr…
cs.LG2023
Confidence-aware Personalized Federated Learning via Variational Expectation Maximization
Junyi Zhu, Xingchen Ma, Matthew B. Blaschko
Federated Learning (FL) is a distributed learning scheme to train a shared model across clients. One common and fundamental challenge in FL is that the sets of data across clients…