## Description

Back to topThis workshop will explore new directions for algebraic statistics in the realm of Bayesian statistics and statistical learning. The considered topics will cover a broad range of problems from modern statistics and machine learning for which underlying algebraic structure provides a common theme. Topics of particular interest are singular models and variational inference, invariance and equivariance in statistics and machine learning, and new interdisciplinary connections between computational algebraic geometry and machine learning.

## Organizers

Back to top## Speakers

Back to top## Schedule

Back to top**Speaker: **Shaowei Lin (Topos Institute)

**Speaker: **Kazuho Watanabe (Toyohashi University of Technology)

**Speaker: **Bryon Aragam (University of Chicago)

**Speaker: **Risi Kondor (University of Chicago)

**Speaker: **Sumio Watanabe (Tokyo Institute of Technology)

**Speaker: **Vishesh Karwa (Temple University)

**Speaker: **Andrew McCormack (Duke University)

**Speaker: **Xuanlong Nguyen (University of Michigan)

**Speaker: **Han Xiao (Rutgers University)

**Speaker: **Judith Rousseau (University of Oxford)

**Speaker: **Kathlén Kohn (KTH Royal Institute of Technology)

**Speaker: **Peter Hoff (Duke University)

**Speaker: **Guido Montufar (UCLA)

**Speaker: **Nadav Dym (Technion – Israel Institute of Technology)

**Speaker: **Sean Plummer (University of Arkansas)

**Speaker: **Jesús De Loera (University of California, Davis (UC Davis))

**Speaker: **Luke Oeding (Auburn University)

**Speaker: **Kathryn Heal (Google)

**Speaker: **Emma Cobian (University of Notre Dame)

**Speaker: **Joe Kileel (University of Texas at Austin)

## Videos

Back to topOnline learning for spiking neural networks with relative information rate

Shaowei Lin

December 11, 2023

Nonstandard minimax rates in nonparametric latent variable models and representation learning

Bryon Aragam

December 11, 2023

Bias and Variance of Bayes Cross Validation in Singular Learning Theory

Sumio Watanabe

December 11, 2023

Minimum distance estimators and inverse bounds for latent probability measures

Xuanlong Nguyen

December 12, 2023

On multivariate deconvolution with Wasserstein loss: minimax rates and Bayesian contraction rates

Judith Rousseau

December 12, 2023

Geometry of Linear Neural Networks that are Equivariant / Invariant under Permutation Groups

Kathlén Kohn

December 13, 2023

Characterizing the spectrum of the neural tangent kernel via a power series expansion

Guido Montufar

December 13, 2023

Homotopy Continuation Techniques for Optimization in Variational Inference

Emma Cobian

December 15, 2023