MMDS workshop origins
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 .
About MMDS FoundationMMDS 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.
Organizing committeeMichael Mahoney (Chair), ICSI and Department of Statistics, UC Berkeley.
Alexander Shkolnik, Department of Economics, UC Berkeley.
Petros Drineas, Department of Computer Science, Rensselaer Polytechnic Institute.