CMU ML talk: Mining Large Time-evolving Data Using Matrix and Tensor Tools

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

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.

The link.