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4 papers · 1 filter
Subspace Clustering through Sub-Clusters
Weiwei Li, Jan Hannig, Sayan Mukherjee
The problem of dimension reduction is of increasing importance in modern data analysis. In this paper, we consider modeling the collection of points in a high dimensional space as…
Scalable Algorithms for Learning High-Dimensional Linear Mixed Models
Zilong Tan, Kimberly Roche, Xiang Zhou +1
Linear mixed models (LMMs) are used extensively to model dependecies of observations in linear regression and are used extensively in many application areas. Parameter estimation f…
Parallelizing MCMC with Random Partition Trees
Xiangyu Wang, Fangjian Guo, Katherine A. Heller +1
The modern scale of data has brought new challenges to Bayesian inference. In particular, conventional MCMC algorithms are computationally very expensive for large data sets. A pro…
Formal Hypothesis Tests for Additive Structure in Random Forests
Lucas Mentch, Giles Hooker
While statistical learning methods have proved powerful tools for predictive modeling, the black-box nature of the models they produce can severely limit their interpretability and…