We consider sequential change-point detection in parallel data streams, where each stream has its own change point. Once a is detected stream, this deactivated permanently. The goal to maximize the normal operation of pre-change while controlling proportion post-change streams among active at all time points. Taking Bayesian formulation, we develop compound decision framework for problem. A pro...

Change detection is an important step for the characterization of object dynamics at earth’s surface. In multi-temporal point clouds, main challenge to detect true changes different granularities in a scene subject significant noise and occlusion. To better understand new research perspectives this field, deep review recent advances 3D change methods needed. end, we present comprehensive state ...

We consider the fundamental problem of matching a template to signal. do so by M-estimation, which encompasses procedures that are robust gross errors (i.e., outliers). Using standard results from empirical process theory, we derive convergence rate and asymptotic distribution M-estimator under relatively mild assumptions. also discuss optimality estimator, both in finite samples minimax sense ...

This manuscript makes two contributions to the field of change-point detection. In a general setting, we provide generic algorithm for aggregating local homogeneity tests into an estimator change-points in time series. Interestingly, establish that error rates collection directly translate detection properties estimator. scheme is then applied various problems including covariance detection, no...

Change point detection in high dimensional data has found considerable interest recent years. Most of the literature either designs methodology for a retrospective analysis, where whole sample is already available when statistical inference begins, or considers online schemes controlling average time until false alarm. This paper takes different view and develops monitoring scenario, arrives su...