Clustering algorithms based on mean shift or spectral methods on graphs are ubiquitous in data analysis. However, in practice, these two types of algorithms are treated as conceptually disjoint: mean shift clusters based on the density of a dataset, while spectral methods allow for clustering based on geometry. In joint work with Nicolás ...
Creator:
Craig, Katy (University of California, Santa Barbara)
Created:
2022-02-15
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
I will share some reminiscences of my many years working with Gunnar. The career that I have had would not have been possible without his kindness, wisdom, and generosity.
Creator:
de Silva, Vin (Pomona College)
Created:
2022-08-04
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
The Gromov-Hausdorff distance between two metric spaces is an important tool in geometry, but it is difficult to compute. For example, the Gromov-Hausdorff distance between unit spheres of different dimensions is unknown in nearly all cases. I will introduce recent work by Lim, Mémoli, and Smith that finds the exact Gromov-Hausdorff distances be...
Creator:
Adams, Henry (Colorado State University)
Created:
2022-08-04
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Configuration spaces of disks in a region of the plane vary according to the radius of the disks, and their topological invariants such as homology also vary. Realizing a given homology class means coordinating the motion of several disks, and if there is not enough space for the disks to move, the homology class vanishes. We explore how cluster...
Creator:
Alpert, Hannah (Auburn University)
Created:
2022-08-01
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Modern learning algorithms such as deep neural networks operate in regimes that defy the traditional statistical learning theory. Neural networks architectures often contain more parameters than training samples. Despite their huge complexity, the generalization error achieved on real data is small. In this talk, we aim to study the generalizati...
Creator:
Seroussi, Inbar (Weizmann Institute of Science)
Created:
2022-04-12
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Many diseases are complex heterogeneous conditions that affect multiple organs in the body and depend on the interplay between several factors that include molecular and environmental factors, thus requiring a holistic approach in understanding the complexity and heterogeneity. In this talk, I will present some of our current statistical and ma...
Creator:
Safo, Sandra (University of Minnesota, Twin Cities)
Created:
2022-02-22
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
In the context of numerical linear algebra algorithms, where it is natural to sacrifice accuracy in return for quicker computation of solutions whose errors are only slightly larger than optimal, the time-accuracy tradeoff of randomized sketching has been well-characterized. Algorithms such as Blendenpik and LSRN have shown that carefully design...
Creator:
Gittens, Alex (Rensselaer Polytechnic Institute)
Created:
2022-01-25
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Margaret Deirdre O'Hartigan is an Irish Catholic transsexual woman, transsexual health and rights activist, writer, and retired secretary and typesetter living in Portland, Oregon. Prior to her retirement, O'Hartigan was involved in a number of trans civil rights and nondiscrimination campaigns in Oregon, Washington, and Minnesota, including suc...
Creator:
O'Hartigan, Margaret Deirdre (interviewee)
Contributor:
Billund-Phibbs, Myra (interviewer, project manager, and transciber)
Created:
2022-04-06
Contributed By:
University of Minnesota Libraries, Jean-Nickolaus Tretter Collection in Gay, Lesbian, Bisexual and Transgender Studies.