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3-1 CMU SCS Roadmap • Motivation • Matrix tools • Tensor tools • Case studies • Tensor Basics • Tucker – Tucker 1 – Tucker 2 – Tucker 3 • PARAFAC • Incrementalization CMU SCS Tensor Basics 3-3 CMU SCS Reminder: SVD – Best rank-k approximation in L2 A m n Σ m n U VT ≈ See also PARAFAC 3-4 CMU SCS Reminder: SVD – Best rank-k approximation in L2 A m n ≈ + σ1u1°v1 σ2u2°v2 See also PARAFAC 3-5 CMU SCS
SIGMOD 2015 TUTORIAL Mining and Forecasting of Big Time-series Data Yasushi Sakurai, Yasuko Matsubara (Kumamoto U) and Christos Faloutsos (CMU/SCS) Description Description (pdf): [PDF] Abstract: Given a large collection of time series, such as web-click logs, electric medical records and motion capture sensors, how can we efficiently and effectively find typical patterns? How can we statistically
Large Graph-Mining: Power Tools and a Practitioner's Guide Tutorial T3 in KDD2009 Abstract How to find patterns in large graphs, spanning Giga and Tera bytes? What are the best tools from matrix algebra, and how can they help us solve graph mining problems? These are exactly the goals of this tutorial. Matrix algebra and graph theory can offer powerful tools and theorems, like SVD, spectral analys
U.S. mail address: Christos Faloutsos Dept. of Computer Science , GHC 7003 Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213-3891 Admin: Oliver Moss email: christos-admin-support AT cs DOT cmu DOT edu If interested in grad studies, postdoc, summer internship, etc: Thank you for your interest! Please see this first. Christos Faloutsos Current Position: Fredkin Professor of Computer
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