The fields of data mining and machine learning have seen increasing use and adaptation of methodologies and algorithms from advanced scientific computing and applied mathematics in general including

- Spectral graph partitioning and clustering
- Linear/quadratic and semi-definite Programming
- Latent Semantic Indexing in Information Retrieval
- Non-linear manifold learning and dimension reduction
- PDE-based approach for image analysis

Many of the above developments have large overlap with those in scientific computing/applied mathematics communities, and there are ample opportunities for cross-fertilization at the interface between data mining/machine learning and scientific computing/applied mathematics in general.

This workshop will present surveys and recent research results on advances in data mining algorithms and methodologies using matrix and graph algorithms and other applied mathematics methods. We hope to bring together leading researchers in data mining, machine learning, applied mathematics and statistical computing to share ideas and form collaboration. There are exciting opportunities in applying and extending methodologies and techniques from scientific computing and applied mathematics to develop efficient and effective algorithms for machine learning and data mining problems. At the same time, ideas and methods from machine learning can contribute to grand-challenge problems in scientific computing and computational science.

Co-Chairs:

Hongyuan Zha Department of Computer Science and Engineering and, by courtesy, Department of Statistics The Pennsylvania State University USA Tel: +1 (814) 863-0608 Fax: +1 (814) 865-3176 E-mail: zha@cse.psu.edu	Chris Ding Computational Research Division Lawrence Berkeley National Laboratory Building 50F, Room 1608 1 Cyclotron Road, Berkeley, California 9472 USA Tel: +1 510-486-6901 Fax: +1 510-486-5548 E-mail: chqding@lbl.gov
Michael Ng Department of Mathematics The University of Hong Kong USA Tel: +1 (852) 2859 2252 Fax: +1 (852) 2559 2225 E-mail: mng@maths.hku.hk	Efstratios Gallopoulos Department of Computer Engineering & Informatics University of Patras 26500 Patras, Greece Tel: +30.261.0996911 Fax +30.261.0969011 E-mail: stratis@ceid.upatras.gr
Vicenc Torra Campus UAB s/n 08193 Bellaterra Catalonia, Spain vtorra@iiia.csic.es Phone: +34-935 809 570 Fax:   +34-935 809 661