3 accepted papers
We study the change point problem that considers alterations in the conditional distribution of an inferential target on a set of covariates. This paired data scenario is in contrast to the standard setting where a sequentially observed variable is analyzed for potential changes in the marginal dist…
We introduce a multi-modes tensor clustering method that implements a fused version of the alternating least squares algorithm (Fused-Orth-ALS) for simultaneous tensor factorization and clustering. The statistical convergence rates of recovery and clustering are established when the data are a nois…
We consider the detection and localization of gradual changes in the distribution of a sequence of time-ordered observations. Existing literature focuses mostly on the simpler abrupt setting which assumes a discontinuity jump in distribution, and is unrealistic for some applied settings. We propose…