activity
20062025
most citedEfficient Computer Network Anomaly Detection by Changepoint Detection Methods

155 citations · 578 across the 27 of their papers we have counts for

collaborators

34 papers

stat.OT2025

Change, dependence, and discovery: Celebrating the work of T.L. Lai

Alexander G. Tartakovsky, Jay Bartroff, Cheng-Der Fuh +1

Tze Leung Lai made seminal contributions to sequential analysis, particularly in sequential hypothesis testing, changepoint detection and nonlinear renewal theory. His work establi…

math.ST2024★ 1 cited

Nearly Optimum Properties of Certain Multi-Decision Sequential Rules for General Non-i.i.d. Stochastic Models

Alexander G. Tartakovsky

Dedicated to the memory of Professor Tze Leung Lai, this paper introduces three multi-hypothesis sequential tests. These tests are derived from one-sided versions of the sequential…

math.ST2024

Beyond boundaries: Gary Lorden's groundbreaking contributions to sequential analysis

Jay Bartroff, Alexander G. Tartakovsky

Gary Lorden provided several fundamental and novel insights into sequential hypothesis testing and changepoint detection. In this article, we provide an overview of Lorden's contri…

math.ST2023

Quickest Changepoint Detection in General Multistream Stochastic Models: Recent Results, Applications and Future Challenges

Alexander G Tartakovsky, Valentin Spivak

Modern information systems generate large volumes of data with anomalies that occur at unknown points in time and have to be detected quickly and reliably with low false alarm rate…

stat.AP2022

Detecting an Intermittent Change of Unknown Duration

Grigory Sokolov, Valentin S. Spivak, Alexander G. Tartakovsky

Oftentimes in practice, the observed process changes statistical properties at an unknown point in time and the duration of a change is substantially finite, in which case one says…

eess.SP2021

Quickest Change Detection with Non-Stationary Post-Change Observations

Yuchen Liang, Alexander G. Tartakovsky, Venugopal V. Veeravalli

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 stationary…