70 citations · 103 across the 11 of their papers we have counts for
11 papers
Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization
Jian Cao, Myeongjong Kang, Felix Jimenez +3
To achieve scalable and accurate inference for latent Gaussian processes, we propose a variational approximation based on a family of Gaussian distributions whose covariance matric…
Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems
Hyunwoong Chang, Changwoo J. Lee, Zhao Tang Luo +2
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…
Why the Rich Get Richer? On the Balancedness of Random Partition Models
Changwoo J. Lee, Huiyan Sang
Random partition models are widely used in Bayesian methods for various clustering tasks, such as mixture models, topic models, and community detection problems. While the number o…
Row-clustering of a Point Process-valued Matrix
Lihao Yin, Ganggang Xu, Huiyan Sang +1
Structured point process data harvested from various platforms poses new challenges to the machine learning community. By imposing a matrix structure to repeatedly observed marked…
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs
Changwoo J. Lee, Zhao Tang Luo, Huiyan Sang
Graphs have been commonly used to represent complex data structures. In models dealing with graph-structured data, multivariate parameters may not only exhibit sparse patterns but…
Risk Based Arsenic Rational Sampling Design for Public and Environmental Health Management
Lihao Yin, Huiyan Sang, Douglas J. Schnoebelen +6
Groundwater contaminated with arsenic has been recognized as a global threat, which negatively impacts human health. Populations that rely on private wells for their drinking water…