Seminars and Colloquia by Series

Cancelled - A refined Brill-Noether theory over Hurwitz spaces

Series
Algebra Seminar
Time
Monday, March 23, 2020 - 15:00 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Hannah Larson – Stanford University –

This talk was cancelled due to the current status. The following is the original abstract for the talk. The celebrated Brill-Noether theorem says that the space of degree $d$ maps of a general genus $g$ curve to $\mathbb{P}^r$ is irreducible. However, for special curves, this need not be the case. Indeed, for general $k$-gonal curves (degree $k$ covers of $\mathbb{P}^1$), this space of maps can have many components, of different dimensions (Coppens-Martens, Pflueger, Jensen-Ranganathan). In this talk, I will introduce a natural refinement of Brill-Noether loci for curves with a distinguished map $C \rightarrow \mathbb{P}^1$, using the splitting type of push forwards of line bundles to $\mathbb{P}^1$. In particular, studying this refinement determines the dimensions of all irreducible components of Brill-Noether loci of general $k$-gonal curves.

Adaptive Tracking and Parameter Identification (cancelled due to COVID-19)

Series
Applied and Computational Mathematics Seminar
Time
Monday, March 23, 2020 - 13:55 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Michael Malisoff – LSU

Adaptive control problems arise in many engineering applications in which one needs to design feedback controllers that ensure tracking of desired reference trajectories while at the same time identify unknown parameters such as control gains. This talk will summarize the speaker's work on adaptive tracking and parameter identification, including an application to curve tracking problems in robotics. The talk will be understandable to those familiar with the basic theory of ordinary differential equations. No prerequisite background in systems and control will be needed to understand and appreciate this talk.

Mathapalooza After Dark!

Series
Other Talks
Time
Monday, March 16, 2020 - 19:00 for 2 hours
Location
Highland Ballroom, 644 North Highland Ave.
Speaker

A math-themed variety show including music, improv comedy, a poetry slam, juggling, a fashion show (audience members can join in)  and more, right there on the stage of the fabulous Highland Ballroom!   Tickets  are $10.00.

Mathapalooza!

Series
Other Talks
Time
Sunday, March 15, 2020 - 13:00 for 4 hours (half day)
Location
MLK Recreation Center, 110 Hilliard St. SE
Speaker

An afternoon of public engagement of mathematics through puzzles, games, and the arts, including:  magic (by Matt Baker), juggling and other circus arts, music, dance, an art gallery, and a live construction of a Fibonacci-based sculpture (by Akio Hizume).  It is free and open to the public, but our partner the Julia Robinson Mathematics Festival recommends registering at https://jrmf.org/event-details/mathapalooza .  If you want to get involved, please contact Evans Harrell directly.

CANCELLED: Online Selection with Cardinality Constraints under Bias

Series
ACO Student Seminar
Time
Friday, March 13, 2020 - 13:05 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Jad Salem – Math, Georgia Tech –
Optimization and machine learning algorithms often use real-world data that has been generated through complex socio-economic and behavioral processes. This data, however, is noisy, and naturally encodes difficult-to-quantify systemic biases. In this work, we model and address bias in the secretary problem, which has applications in hiring. We assume that utilities of candidates are scaled by unknown bias factors, perhaps depending on demographic information, and show that bias-agnostic algorithms are suboptimal in terms of utility and fairness. We propose bias-aware algorithms that achieve certain notions of fairness, while achieving order-optimal competitive ratios in several settings.
 

Complexity of the pure spherical p-spin model

Series
Stochastics Seminar
Time
Thursday, March 12, 2020 - 15:05 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Julian Gold – Northwestern University –

The pure spherical p-spin model is a Gaussian random polynomial H of degree p on an N-dimensional sphere, with N large. The sphere is viewed as the state space of a physical system with many degrees of freedom, and the random function H is interpreted as a smooth assignment of energy to each state, i.e. as an energy landscape. 

In 2012, Auffinger, Ben Arous and Cerny used the Kac-Rice formula to count the average number of critical points of H having a given index, and with energy below a given value. This number is exponentially large in N for p > 2, and the rate of growth itself is a function of the index chosen and of the energy cutoff. This function, called the complexity, reveals interesting topological information about the landscape H: it was shown that below an energy threshold marking the bottom of the landscape, all critical points are local minima or saddles with an index not diverging with N. It was shown that these finite-index saddles have an interesting nested structure, despite their number being exponentially dominated by minima up to the energy threshold. The total complexity (considering critical points of any index) was shown to be positive at energies close to the lowest. Thus, at least from the perspective of the average number of critical points, these random landscapes are very non-convex. The high-dimensional and rugged aspects of these landscapes make them relevant to the folding of large molecules and the performance of neural nets. 

Subag made a remarkable contribution in 2017, when he used a second-moment approach to show that the total number of critical points concentrates around its mean. In light of the above, when considering critical points near the bottom of the landscape, we can view Subag's result as a statement about the concentration of the number of local minima. His result demonstrated that the typical behavior of the minima reflects their average behavior. We complete the picture for the bottom of the landscape by showing that the number of critical points of any finite index concentrates around its mean. This information is important to studying associated dynamics, for instance navigation between local minima. Joint work with Antonio Auffinger and Yi Gu at Northwestern. 

Cancelled

Series
Math Physics Seminar
Time
Thursday, March 12, 2020 - 15:00 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Wei Li – Louisiana State University –

The Neumann-Poincaré (NP) operator arises in boundary value problems, and plays an important role in material design, signal amplification, particle detection, etc. The spectrum of the NP operator on domains with corners was studied by Carleman before tools for rigorous discussion were created, and received a lot of attention in the past ten years. In this talk, I will present our discovery and verification of eigenvalues embedded in the continuous spectrum of this operator. The main ideas are decoupling of spaces by symmetry and construction of approximate eigenvalues. This is based on two works with Stephen Shipman and Karl-Mikael Perfekt.

Cancelled

Series
School of Mathematics Colloquium
Time
Thursday, March 12, 2020 - 11:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Oscar Bruno – Caltech, Computing and Mathematical Sciences

Robustly Clustering a Mixture of Gaussians

Series
High Dimensional Seminar
Time
Wednesday, March 11, 2020 - 15:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Santosh Vempala – Georgia Tech

Please Note: We give an efficient algorithm for robustly clustering of a mixture of two arbitrary Gaussians, a central open problem in the theory of computationally efficient robust estimation, assuming only that the the means of the component Gaussians are well-separated or their covariances are well-separated. Our algorithm and analysis extend naturally to robustly clustering mixtures of well-separated logconcave distributions. The mean separation required is close to the smallest possible to guarantee that most of the measure of the component Gaussians can be separated by some hyperplane (for covariances, it is the same condition in the second degree polynomial kernel). Our main tools are a new identifiability criterion based on isotropic position, and a corresponding Sum-of-Squares convex programming relaxation. This is joint work with He Jia.

Pages