MS-16 Linear Algebra and Positivity with Applications to Data Science (Positivity with Applications)
Organizers: Dominique Guillot (University of Delaware), Apoorva Khare (Indian Institute of Science), and Bala Rajaratnam (Stanford University)
Making sense of vast amounts of data has become one of the great challenges of the 21st century. This mini-symposium will highlight how recent advances in analysis (in particular positivity and related topics), linear algebra, algebraic geometry, and statistics provide new tools to analyze data in areas such as covariance estimation and the theory of graphical models.
More information regarding this mini-symposium can be found hereSpeakers
Mahya Ghandehari, LAA Early Career Speaker, Geometric graphs and uniform embeddings
Alexander Belton, A quantitative form of Schoenberg's theorem in fixed dimension
Peter Diao, Distribution-Free Consistency of Graph Clustering
Shaun Fallat, Hadamard Powers, Critical Exponents, and Total Positivity
Alfred Hero, Continuum limits for shortest paths
Ilse Ipsen, Randomized matrix-free trace and log-determinant estimators
Tanvi Jain, Hadamard powers of two classes of positive matrices
Helene Massam, Precision matrix estimation and sampling in coloured graphical Gaussian models
Nikolas Stott, Minimal upper bounds in the Loewner order: characterizations and parametrization.
Caroline Uhler, Your dreams may come true with MTP2
Cynthia Vinzant, Hyperbolicity and reciprocal linear spaces