PhD Dissertation Defense - Ang Li

Title: Revisiting FastMap: New Applications
 
Date: Thursday, June 20th, 2024 - 2:00p - 3:30p
 
Location: SAL 213
 
Committee Members: T. K. Satish Kumar (Chair), John Carlsson, Emilio Ferrara, Sven Koenig, and Aiichiro Nakano
 
Abstract: FastMap was first introduced in the Data Mining community for generating Euclidean embeddings of complex objects. In this talk, I will first generalize FastMap to generate Euclidean embeddings of graphs in near-linear time: The pairwise Euclidean distances approximate a desired graph-based distance function on the vertices. I will then apply the graph version of FastMap to efficiently solve various graph-theoretic problems of significant interest in AI: including facility location, top-K centrality computations, community detection and block modeling, and graph convex hull computations. I will also present a novel learning framework, called FastMapSVM, by combining FastMap and Support Vector Machines. I will then apply FastMapSVM to predict the satisfiability of Constraint Satisfaction Problems and to classify seismograms in Earthquake Science.
 
Zoom Link: https://usc.zoom.us/j/92402869565?pwd=L0dwc0xRZVNrT3UrQWZCcERmVlBqQT09

Location: Henry Salvatori Computer Science Center (SAL) - 213

Audiences: Everyone Is Invited

Contact: Ang Li

Event Link: https://usc.zoom.us/j/92402869565?pwd=L0dwc0xRZVNrT3UrQWZCcERmVlBqQT09