Time: Wednesday, November 20, from 2:30 to 3:30 pm

 

 

Zoom link for online audience: https://wayne-edu.zoom.us/j/92845590121?pwd=CpRA5Wa5gzSMn2xiVkR2abD83O5nrH.1

Title: Optimal detection of spatial anomaly regions

 

Abstract: There has been a growing interest in multiple changepoints/anomaly detection problems recently, whilst their focuses are mostly on changes taking place on the time index. In this work, we investigate the anomaly-in-mean model on a multidimensional spatial lattice, that is, to detect the number and locations of anomaly spatial regions from the baseline. In addition to the usual minimisation over cost function with a penalisation related to the number of anomalies, we also introduce a new penalty on the area of minimum convex hull that covers the anomaly regions. We show that our estimation on the number and locations of anomalies are consistent, and prove that the method achieves optimal estimation error under the minimax framework. We also proposed a dynamic programming algorithm to solve the penalised cost detection problem approximately and carry out large-scale Monte Carlo simulations to examine the performance of the proposed methodology.

 

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The CAD Seminar Series is a dedicated platform for advancing knowledge, fostering innovation, and promoting collaboration across the fields of Computation, Artificial Intelligence, and Data Science. This series brings together leading experts, researchers, and professionals to explore the latest developments, tackle emerging challenges, and drive forward-thinking solutions at the convergence of these critical disciplines.

 

Objectives:

 

• Advance Knowledge: Share cutting-edge research and insights that push the boundaries of what is known in CAD.

• Foster Innovation: Encourage the development of novel ideas and solutions through interdisciplinary dialogue and creative thinking.

• Promote Collaboration: Unite expertise across disciplines and build bridges between academia, industry, and government to address complex problems and create opportunities for joint ventures.

Schedule: The seminars will be held on a weekly basis (unless otherwise noted) throughout the academic year. For Fall 2024, the seminars are tentatively scheduled for Wednesdays from 2:30 PM to 3:30 PM, and will be available both in-person at 1146 FAB and online. Each seminar will spotlight a particular topic, providing an in-depth exploration and fostering lively discussions. 

 

Target Audience: The CAD Seminar Series is designed for a diverse audience, including faculty, researchers, students, and professionals in Computation, AI, Data Science, and related fields. It serves as a forum for exchanging ideas, networking, and contributing to the growth of these rapidly evolving areas. We highly recommend in-person attendance to enhance engagement and networking opportunities with speakers and fellow participants.

 

Call for Participation: We welcome contributions from researchers, practitioners, and students. Whether presenting your work, participating in discussions, or attending as a learner, your involvement is crucial to the success of this collaborative initiative. 

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