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Hyunwoong Chang

2 accepted papers

2022

Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems

NeurIPS 2022accept

The multiple-try Metropolis (MTM) algorithm is an extension of the Metropolis-Hastings (MH) algorithm by selecting the proposed state among multiple trials according to some weight function. Although MTM has gained great popularity owing to its faster empirical convergence and mixing than the standa…

2020

Lipschitz Continuous Autoencoders in Application to Anomaly Detection

AISTATS 2020poster

Anomaly detection is the task of finding abnormal data that are distinct from normal behavior. Current deep learning-based anomaly detection methods train neural networks with normal data alone and calculate anomaly scores based on the trained model. In this work, we formalize current practices, bui…