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Low rank matrix recovery is about reconstructing a low rank matrix from incomplete measurements. It arises frequently in many research areas of science and engineering, for example, machine learning, ...
We are delighted to organize and host the second edition of the biennial Summer School on Random Matrices at the University of Michigan during June 18--29, 2018.We thank the Michigan Center for Applie...
Rajendra Bhatia has made remarkable contributions to Mathematics research and teaching, and to growth of Mathematics in India. He has been honored with various awards including the Medal for Young Sci...
Matrix and tensor factorizations have a long history in machine learning. Being able to recover latent factors in the data and flexible enough to accommodate a large set of constraints and regularizat...
The Gordon Research Seminar on Matrix Metalloproteinases is a unique forum for graduate students, post-docs, and other scientists with varying levels of experience and education to present and exchang...
Since their discovery as tissue remodeling enzymes over 50 years ago, the matrix metalloproteinases (MMPs) and the related ADAM and ADAMTS families have been identified as major contributors to human ...
Purpose: The workshop aims to stimulate research and interaction of mathematicians and scientists in all aspects of linear algebra and matrix analysis and their applications and to provide an opport...
Following the success of five previous conferences held in Flint (1995), Winnipeg (1998), Leuven (2000), Adelaide (2002), and Pisa (2005), the sixth international conference on matrix-analytic methods...

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