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How Well Can We Generalize Nonlinear Learning Models in High Dimensions??
Description:
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.
Last Updated:
2022-04-22
How Well Can We Generalize Nonlinear Learning Models in High Dimensions??
Integrative Discriminant Analysis Methods for Multi-view Data
Description:
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.
Last Updated:
2022-04-22
Integrative Discriminant Analysis Methods for Multi-view Data
Intelligent Randomized Algorithms for the Low CP-Rank Tensor Approximation Problem
Description:
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.
Last Updated:
2022-04-22
Intelligent Randomized Algorithms for the Low CP-Rank Tensor Approximation Problem
Interview with Margaret Deirdre O'Hartigan
Description:
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.
Page Count:
2
Last Updated:
2022-04-11
Interview with Margaret Deirdre O'Hartigan
Lecture (Remotely)
Creator:
Kalisnik, Sara (ETH Zürich)
Created:
2022-08-04
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Lecture (Remotely)
Lillian Gamm
Description:
Lillian Gamm arrived at Ellis Island from Russia on April 19, 1910. While living in Manhattan, she worked hard as a bookkeeper, raised a family, and pursued her dreams.
Creator:
Feldman, Jonah
Contributor:
Rolland, Isabella
Created:
2022-05-02
Contributed By:
University of Minnesota, Immigration History Research Center
Last Updated:
2022-05-11
Lillian Gamm
Limits of Dense Simplicial Complexes
Description:
We develop a theory of limits for sequences of dense abstract simplicial complexes, where a sequence is considered convergent if its homomorphism densities converge. The limiting objects are represented by stacks of measurable [0,1]-valued functions on unit cubes of increasing dimension, each corresponding to a dimension of the abstract simplici...
Creator:
Segarra, Santiago (Rice University)
Created:
2022-08-01
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Limits of Dense Simplicial Complexes
Luu Nhat Tam Ngyuen
Description:
Luu Nhat Tam Ngyuen moved to the U.S. with her mom and dad in 2019. Unfortunately, her sister was not able to join them because of her age. Luu Nhat Tam is the only person who can speak English in her family.
Creator:
Nguyen, Luu Nhat Tam
Contributor:
Rolland, Isabella
Created:
2022-05-09
Contributed By:
University of Minnesota, Immigration History Research Center
Last Updated:
2022-05-11
Luu Nhat Tam Ngyuen
Method of Moments: From Sample Complexity to Efficient Implicit Computations
Description:
In this talk, I focus on the multivariate method of moments for parameter estimation. First from a theoretical standpoint, we show that in problems where the noise is high, the number of observations necessary to estimate parameters is dictated by the moments of the distribution. Second from a computational standpoint, we address the curse of di...
Creator:
Pereira, Joao (The University of Texas at Austin)
Created:
2022-04-05
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-04-22
Method of Moments: From Sample Complexity to Efficient Implicit Computations
Motivic Euler characteristics and the Motivic Segal-Becker theorem (Remotely)
Description:
A well-known and very useful result in algebraic topology is the statement that the Euler characteristic of G/N(T) in singular cohomology is 1, where G is a compact Lie group and N(T) is the normalizer of a maximal torus. In the presence of a transfer map as constructed by Becker and Gottlieb the above result shows that in any generalized cohomo...
Creator:
Joshua, Roy (The Ohio State University)
Created:
2022-08-02
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Motivic Euler characteristics and the Motivic Segal-Becker theorem (Remotely)
On Multiclass Adversarial Training, Perimeter Minimization, and Multimarginal Optimal Transport Problems
Description:
Adversarial training is a framework widely used by machine learning practitioners to enforce robustness of learning models. Despite the development of several computational strategies for adversarial training and some theoretical development in the broader distributionally robust optimization literature, there are still several theoretical quest...
Creator:
Garcia Trillos, Nicolas (University of Wisconsin, Madison)
Created:
2022-03-01
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-04-22
On Multiclass Adversarial Training, Perimeter Minimization, and Multimarginal Optimal Transport Problems
Path induction and the indiscernibility of identicals
Description:
Mathematics students learn a powerful technique for proving theorems about an arbitrary natural number: the principle of mathematical induction. This talk introduces a closely related proof technique called "path induction," which can be thought of as an expression of Leibniz's "indiscernibility of identicals": if x and y are identified, then th...
Creator:
Riehl, Emily (Johns Hopkins University)
Created:
2022-08-03
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Path induction and the indiscernibility of identicals
Persistent cup-length
Description:
Cohomological ideas have recently been injected into persistent homology and have for example been used for accelerating the calculation of persistence diagrams by softwares, such as Ripser. The cup product operation which is available at cohomology level gives rise to a graded ring structure that extends the usual vector space structure and is ...
Creator:
Zhou, Ling (The Ohio State University)
Created:
2022-08-02
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Persistent cup-length
Persistent homology and its fibre (Remotely)
Description:
Persistent homology is a main tool in topological data analysis. So it is natural to ask how strong this quantifier is and how much information is lost. There are many ways to ask this question. Here we will concentrate on the case of level set filtrations on simplicial sets. Already the example of a triangle yields a rich structure with the Möb...
Creator:
Tillmann, Ulrike (University of Oxford)
Created:
2022-08-03
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Persistent homology and its fibre (Remotely)
Ramification in Higher Algebra
Description:
I will review the theory of ramification in number theory and then show that being totally ramified or unramified is equivalent to a natural condition in higher algebra. This leads to a much simplified calculation of THH of a ring of integers in a number field, relying on ramified descent (a kind of weaker etale descent).
Creator:
Berman, John (University of Massachusetts)
Created:
2022-08-03
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Ramification in Higher Algebra
Relaxing Gaussian Assumptions in High Dimensional Statistical Procedures
Description:
The assumption that high dimensional data is Gaussian is pervasive in many statistical procedures, due not only to its tail decay, but also to the level of analytic tractability this special distribution provides. We explore the relaxation of the Gaussian assumption in Single Index models and Shrinkage estimation using two tools that originate i...
Creator:
Goldstein, Larry (University of Southern California)
Created:
2022-03-29
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-04-22
Relaxing Gaussian Assumptions in High Dimensional Statistical Procedures
Sarah Reyes
Description:
Sarah Reyes was born in the Phlippines and moved to the U.S. when she was in middle school. Though she faced a lot of racial discrimination in her first years of being here, she eventually found a Filipino American community that she is proud to be a part of now.
Creator:
Haakonsen, Malia
Contributor:
Rolland, Isabella
Created:
2022-05-02
Contributed By:
University of Minnesota, Immigration History Research Center
Last Updated:
2022-05-11
Sarah Reyes
Simplifying Federated Learning Jobs With Flame
Description:
Federated machine learning (FL) is gaining a lot of traction across research communities and industries. FL allows machine learning (ML) model training without sharing data across different parties, thus natively supporting data privacy. However, designing and executing FL jobs is not an easy task today. Flame is an open-source project that aims...
Creator:
Le, Myungjin (Cisco)
Created:
2022-04-29
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Simplifying Federated Learning Jobs With Flame
Speculations
Description:
I would like to talk about the interaction of traditional algebraic topology and homotopy theory with applied topology, and specifically describe specifically some opportunities for better integration of "higher tech" techniques into applications.
Creator:
Carlsson, Gunnar (Stanford University)
Created:
2022-08-05
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-09-06
Speculations
Stability and Generalization in Graph Convolutional Neural Networks
Description:
In recent years, the need to accommodate non-Euclidean structures in data science has brought a boom in deep learning methods on graphs, leading to many practical applications with commercial impact. In this talk, we will review the mathematical foundations of the generalization capabilities of graph convolutional neural networks (GNNs). We will...
Creator:
Levie, Ron (Ludwig-Maximilians-Universität München)
Created:
2022-02-01
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Last Updated:
2022-04-22
Stability and Generalization in Graph Convolutional Neural Networks