Mining Large Time-evolving Data Using Matrix and Tensor Tools
ICML 2007 tutorial, Cornvallis, OR, USA


Christos Faloutsos, CMU
Tamara G. Kolda, Sandia National Labs
Jimeng Sun, CMU

DESCRIPTION - OBJECTIVES

How can we find patterns in sensor streams (eg., a sequence of temperatures, water-pollutant measurements, or machine room measurements)? How can we mine Internet traffic graph over time? Further, how can we make the process incremental? We review the state of the art in four related fields: (a) numerical analysis and linear algebra (b) multi-linear/tensor analysis (c) graph mining and (d) stream mining. We will present both theoretical results and algorithms as well as case studies on several real applications. Our emphasis is on the intuition behind each method, and on guidelines for the practitioner.

CONTENT AND OUTLINE

Foils in pdf

WHO SHOULD ATTEND

Researchers who want to get up to speed with the major tools in stream mining, graph mining. Also, practitioners who want a concise, intuitive overview of the state of the art. 

ABOUT THE INSTRUCTORS


Last updated: June 22, 2007