Multiple domains involve systems with abruptly changing states, that result in signals with
signatures that are corrupted by noise and sensor dynamics. In many applications, prior …

The evolution potential estimation of news events can support the decision making of both
corporations and governments. For example, a corporation could manage its public relations …

In this paper, a novel procedure for regression analysis in the case of non-stationary data
streams is presented. Despite numerous applications, the regression task is rarely …

The problem of quickest detection of a change in the distribution of a sequence of
independent observations is considered. The pre-change observations are assumed to be …

A model can be easily influenced by unseen factors in nonstationary environments and fail
to fit dynamic data distribution. In a classification scenario, this is known as a concept drift …

Learning from noisy data is a challenging task especially when the system under
consideration has a non-stationary nature. The source of the noise is often assumed to be …

We propose a new approach for dealing with the estimation of the location of change-points
in one-dimensional piecewise constant signals observed in white noise. Our approach …

Data generated from naturally occurring processes tends to be non-stationary. For example,
seasonal and gradual changes in climate data and sudden changes in financial data. In …

Dynamical systems with binary-valued observations are widely used in information industry,
technology of biological pharmacy and other fields. Though there have been much efforts …

The utilization of online stochastic algorithms is popular in large-scale learning settings due
to their ability to compute updates on the fly, without the need to store and process data in …