Contact Info
Department of Applied Mathematics
University of Waterloo
Waterloo, Ontario
Canada N2L 3G1
Phone: 519-888-4567, ext. 32700
Fax: 519-746-4319
PDF files require Adobe Acrobat Reader
M3 4206 and Zoom (please email amgrad@uwaterloo.ca for the meeting link)
Esha Saha | Applied Mathematics, University of Waterloo
Expanding the Scope of Random Feature Models: Theory and Applications
Data, defined as facts and statistics collected together for analysis is at the core of every inference or decision made by any living organism. With the advent of technology, humans have been trying to develop methods that can learn from data and generalize well based on past information. It is important to understand the workings of these methods to be able to quantify the cause and nature of the error they can make so that informed decisions can be made using these results. One such method that particularly caught the attention of researchers recently is the random feature model (RFM), introduced for reducing the complexity and faster computation of kernel methods in large-scale machine learning algorithms. This thesis aims to explore RFMs by expanding their theory and applications in the machine-learning community. We begin our exploration by developing a fast algorithm for high dimensional additive function approximation using a random feature-based surrogate model. Extending the idea of learning functions, we build a model to learn and predict the dynamics of an epidemic from incomplete and scarce data. This model combines the idea of random feature approximation with the use of Takens' delay embedding theorem on the given input data. In our final project, motivated to work on the idea of multiple layers in an RFM, we propose an interpretable deep RFM whose architecture is inspired by diffusion models.
Contact Info
Department of Applied Mathematics
University of Waterloo
Waterloo, Ontario
Canada N2L 3G1
Phone: 519-888-4567, ext. 32700
Fax: 519-746-4319
PDF files require Adobe Acrobat Reader
The University of Waterloo acknowledges that much of our work takes place on the traditional territory of the Neutral, Anishinaabeg and Haudenosaunee peoples. Our main campus is situated on the Haldimand Tract, the land granted to the Six Nations that includes six miles on each side of the Grand River. Our active work toward reconciliation takes place across our campuses through research, learning, teaching, and community building, and is co-ordinated within the Office of Indigenous Relations.