29 citations · 34 across the 4 of their papers we have counts for
5 papers
Spectral Top-Down Recovery of Latent Tree Models
Yariv Aizenbud, Ariel Jaffe, Meng Wang +5
Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying…
Local Two-Sample Testing over Graphs and Point-Clouds by Random-Walk Distributions
Boris Landa, Rihao Qu, Joseph Chang +1
Rejecting the null hypothesis in two-sample testing is a fundamental tool for scientific discovery. Yet, aside from concluding that two samples do not come from the same probabilit…
Spectral neighbor joining for reconstruction of latent tree models
Ariel Jaffe, Noah Amsel, Yariv Aizenbud +3
A common assumption in multiple scientific applications is that the distribution of observed data can be modeled by a latent tree graphical model. An important example is phylogene…
A Deep Learning Approach to Unsupervised Ensemble Learning
Uri Shaham, Xiuyuan Cheng, Omer Dror +4
We show how deep learning methods can be applied in the context of crowdsourcing and unsupervised ensemble learning. First, we prove that the popular model of Dawid and Skene, whic…
Reconsidering the asymptotic null distribution of likelihood ratio tests for genetic linkage in multivariate variance components models
Summer S. Han, Joseph T. Chang
Accurate knowledge of the null distribution of hypothesis tests is important for valid application of the tests. In previous papers and software, the asymptotic null distribution o…