School of Computer Science
Technical Workshop Series
Advanced topics on Data clustering
Presenter: – PhD Candidate Ali Abbasi Tadi
Date/Time: Monday, October 23rd 3:00 pm – 4:00 pm
Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
LATECOMERS WILL NOT BE ADMITTED once the presentation has begun.
Abstract:
Clustering is a way of grouping data points into different clusters consisting of similar data points. The objects with possible similarities remain in a group that has less or no similarities with another group. In this workshop, we explore advanced topics in data clustering for high dimensions. We will define the curse of dimensionality and dimensionality reduction methods like t-SNE, PCA, and Isomap, as well as their implementations. We will explore the consensus matrix and how to adjust the best clustering parameters.
Workshop Outline:
DBSCAN, PCA, Isomap, t-SNE, Consensus matrix, Consensus learning
Prerequisites:
Basic Statistics concepts, matrix algebra, eigenvectors, basic Python programming
Biography:
Ali is pursuing his Ph.D. in computer science at the University of Windsor. His main research interest is security/privacy in machine learning. He has publications on private clustering in top conferences and peer-reviewed journals. He has received various scholarships from the University of Windsor and got 5th place in the iDash Security 2022 competition. He has been invited as a speaker at the Advanced Computing Hub at the University of Windsor. He is serving on the program committee and editorial board of some conferences and journals. He is currently developing privacy attacks on large language models