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Dynamic Algorithms for k Center Problems
PhD Thesis Proposal Defence Title: "Dynamic Algorithms for k Center Problems" by Mr. Jinxiang GAN Abstract: Clustering has many applications in multiple areas, e.g., operations research and machine learning. The k-center problem is one of the most basic clustering problems. Over the last few decades, there has been much work on the k-center problem and its variants. The k center problem aims to place at most k centers that service all clients, trying to minimize the service cost which is the maximum over all clients of the minimum work required for the client to be serviced by one of the centers (this is usually just the min distance from a client to one of the centers.) The standard k-center problem is known to be NP-hard to approximate with a factor smaller than 2 for arbitrary metric spaces[71]. 2-approximation algorithms for this problem are well-known. There are variations of the k center problem that arise in practice, for example, the Euclidean k center problem, the k center problem with outliers, and the fair k center problem. Let P be a set of points in some metric space. In many practical applications, the data set P is not static but changes dynamically over time, e.g, a new point may be inserted to or deleted from P at each step. The solution of the problem then needs to be recomputed at selected query times. If only insertions are permitted, the problem is incremental; if both insertions and deletions are permitted, the problem is fully dynamic. In this proposal, we study some dynamic versions for the k center problems and variants. We propose some dynamic algorithms, and give theoretical analysis of these algorithms. Date: Monday, 8 May 2023 Time: 10:00am - 12:00noon Zoom Meeting: https://hkust.zoom.us/j/94453044219?pwd=M0oyMzZwMkZhQmYySlNUWHdwYmlhUT09 Committee Members: Prof. Mordecai Golin (Supervisor) Prof. Ke Yi (Chairperson) Prof. Siu-Wing Cheng Dr. Amir Goharshady **** ALL are Welcome ****