Technical Workshop Series
Advanced Data Clustering Methods (1st Offering)
Presenter: Ali Abbasi Tadi
Date: Wednesday, June 5th, 2024
Time: 2:30 PM
Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
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 privacy-preserving machine learning. He has publications on private computing in top-tier conferences and peer-reviewed journals. He has received various scholarships from the University of Windsor and got 5th place in the iDash Security Competition 2022. He has been awarded for the best paper in Canadian AI 2022. He is currently developing a secure transformer framework for private computation in the cloud environment.