MMDS workshop origins

The very first Workshop on Modern Massive Data Sets (MMDS) was held on the Stanford University campus, June 21-24, 2006. The objectives were to explore novel techniques for modeling and analyzing massive, high-dimensional, and nonlinearly structured data sets, and to bring together computer scientists, computational and applied mathematicians, statisticians, and practitioners to promote cross-fertilization of ideas. The program, with 45 talks and 24 poster presentations, drew 232 participants- far exceeding the anticipated 75!
MMDS Organizers 2006

MMDS 2006 grew out of discussions among the four organizers (Lek-Heng Lim, Petros Drineas, Michael Mahoney and Gene Golub pictured on the left) about the complementary perspectives brought by the numerical linear algebra (NLA) and the theoretical computer science (TCS) communities to linear algebra and matrix computations. These discussions were motivated by data applications, and, in particular, by technological developments over the last two decades (in both scientific and Internet domains) that permit the automatic generation of very large data sets.

The workshop was loosely organized around six hour-long tutorials that introduced participants to the four major themes of the workshop: (1) linear algebraic basics, (2) industrial applications and sampling methods, (3) kernel and learning applications, (4) tensor-based data applications. For more details read our SIAM News letter Bridging the Gap Between Numerical Linear Algebra, Theoretical Computer Science, and Data Applications .


Clip-36x36

About MMDS Foundation

MMDS Foundation began in 2006 with the purpose of promoting the development of next-generation of algorithmic, mathematical and statistical analysis methods for complex, large-scale data sets with applications within academia, industry and government. Since then it has orginized an academic workshop on Modern Massive Data Sets (MMDS). Every two years, this meeting brings together computer scientists, statisticians, mathematicians, and data analysis practitioners from academia, government and industry. The workshop includes a fully packed week of talks from experts in various fields as well as workshop sessions and poster presentations. Materials are archived for public access on our meetings page. MMDS foundation is committed to fostering cross-fertilization of ideas among participants from various disciplines and to serving as a resource for state of the art in large-scale data set analysis.
Academic-icon-36x36

Organizing committee

Michael Mahoney (Chair), ICSI and Department of Statistics, UC Berkeley.
Alexander Shkolnik, Institute for Computational Mathematics and Engineering, Stanford University.
Petros Drineas, Department of Computer Science, Rensselaer Polytechnic Institute.
Reza Zadeh, Institute for Computational Mathematics and Engineering, Stanford University.
Fernando Perez, Henry H. Wheeler Jr. Brain Imaging Center, UC Berkeley.