Difference between revisions of "Past Probability Seminars Spring 2020"

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__NOTOC__
 
__NOTOC__
  
== Spring 2011 ==
+
= Spring 2020 =
  
 +
<b>Thursdays in 901 Van Vleck Hall at 2:30 PM</b>, unless otherwise noted.
 +
<b>We  usually end for questions at 3:20 PM.</b>
  
Thursdays in 901 Van Vleck Hall at 2:25 PM, unless otherwise noted. If you would like to receive announcements about upcoming seminars, please visit [https://www-old.cae.wisc.edu/mailman/listinfo/apseminar this page] to sign up for the email list.
+
If you would like to sign up for the email list to receive seminar announcements then please send an email to
 +
[mailto:join-probsem@lists.wisc.edu join-probsem@lists.wisc.edu]
  
 +
 +
== January 23, 2020, [https://www.math.wisc.edu/~seppalai/ Timo Seppalainen] (UW Madison) ==
 +
'''Non-existence of bi-infinite geodesics in the exponential corner growth model
 +
'''
 +
 +
Whether bi-infinite geodesics exist has been a significant open problem in first- and last-passage percolation since the mid-80s.  A non-existence proof  in the case of directed planar last-passage percolation with exponential weights was posted by Basu, Hoffman and Sly in  November 2018. Their proof utilizes estimates from integrable probability.    This talk describes an independent proof completed 10 months later that relies on couplings, coarse graining, and control of geodesics through planarity and increment-stationary last-passage percolation. Joint work with Marton Balazs and Ofer Busani (Bristol).
 +
 +
== January 30, 2020, [https://www.math.wisc.edu/people/vv-prof-directory Scott Smith] (UW Madison) ==
 +
'''Quasi-linear parabolic equations with singular forcing'''
  
[[Past Seminars]]
+
The classical solution theory for stochastic ODE's is centered around Ito's stochastic integral.  By intertwining ideas from analysis and probability, this approach extends to many PDE's, a canonical example being multiplicative stochastic heat equations driven by space-time white noise.  In both the ODE and PDE settings, the solution theory is beyond the scope of classical deterministic theory because of the ambiguity in multiplying a function with a white noise.  The theory of rough paths and regularity structures provides a more quantitative understanding of this difficulty, leading to a more refined solution theory which efficiently divides the analytic and probabilistic aspects of the problem, and remarkably, even has an algebraic component.
 +
 
 +
In this talk, we will discuss a new application of these ideas to stochastic heat equations where the strength of the diffusion is not constant but random, as it depends locally on the solution.  These are known as quasi-linear equations.  Our main result yields the deterministic side of a solution theory for these PDE's, modulo a suitable renormalization.  Along the way, we identify a formally infinite series expansion of the solution which guides our analysis, reveals a nice algebraic structure, and encodes the counter-terms in the PDE.  This is joint work with Felix Otto, Jonas Sauer, and Hendrik Weber.
 +
 
 +
== February 6, 2020, [https://sites.google.com/site/cyleeken/ Cheuk-Yin Lee] (Michigan State) ==
 +
'''Sample path properties of stochastic partial differential equations: modulus of continuity and multiple points'''
 +
 
 +
In this talk, we will discuss sample path properties of stochastic partial differential equations (SPDEs). We will present a sharp regularity result for the stochastic wave equation driven by an additive Gaussian noise that is white in time and colored in space. We prove the exact modulus of continuity via the property of local nondeterminism. We will also discuss the existence problem for multiple points (or self-intersections) of the sample paths of SPDEs. Our result shows that multiple points do not exist in the critical dimension for a large class of Gaussian random fields including the solution of a linear system of stochastic heat or wave equations.
 +
 
 +
== February 13, 2020, [http://www.jelena-diakonikolas.com/ Jelena Diakonikolas] (UW Madison) ==
 +
'''Langevin Monte Carlo Without Smoothness'''
 +
 
 +
Langevin Monte Carlo (LMC) is an iterative algorithm used to generate samples from a distribution that is known only up to a normalizing constant. The nonasymptotic dependence of its mixing time on the dimension and target accuracy is understood mainly in the setting of smooth (gradient-Lipschitz) log-densities, a serious limitation for applications in machine learning. We remove this limitation by providing polynomial-time convergence guarantees for a variant of LMC in the setting of non-smooth log-concave distributions. At a high level, our results follow by leveraging the implicit smoothing of the log-density that comes from a small Gaussian perturbation that we add to the iterates of the algorithm and while controlling the bias and variance that are induced by this perturbation.
 +
Based on joint work with Niladri Chatterji, Michael I. Jordan, and Peter L. Bartlett.
 +
 
 +
== February 20, 2020, [https://math.berkeley.edu/~pmwood/ Philip Matchett Wood] (UC Berkeley) ==
 +
'''A replacement principle for perturbations of non-normal matrices'''
 +
 
 +
There are certain non-normal matrices whose eigenvalues can change dramatically when a small perturbation is added.  However, when that perturbation is an iid random matrix, it appears that the eigenvalues become stable after perturbation and only change slightly when further small perturbations are added.  Much of the work is this situation has focused on iid random gaussian perturbations.  In this talk, we will discuss work on a universality result that allows for consideration of non-gaussian perturbations, and that shows that all perturbations satisfying certain conditions will produce the same limiting eigenvalue measure.  Interestingly, this even allows for deterministic perturbations to be considered.  Joint work with Sean O'Rourke.
  
 +
== February 27, 2020, No seminar ==
 +
''' '''
  
==Monday, January 24, 2:25PM, B129 [http://www.math.brown.edu/~schhita/ Sunil Chhita (Brown University)==
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== March 5, 2020, [https://www.ias.edu/scholars/jiaoyang-huang Jiaoyang Huang] (IAS) ==
<span style="color:#FF0000">'''UNUSUAL TIME AND PLACE'''<span style="color:#009000">
+
''' Large Deviation Principles via Spherical Integrals'''
:Title: '''Particle Systems arising from an Anti-ferromagnetic Ising Model'''
 
  
:Abstract: We present a low temperature anisotropic anti-ferromagnetic 2D Ising model through the guise of a certain dimer model. This model also has a bijection with a one-dimensional particle system equipped with creation and annihilation. We can find the exact phase diagram, which determines two significant values (the independent and critical value).  We also highlight some of the behavior of the model in the scaling window at criticality and at independence.
+
In this talk, I'll explain a framework to study the large deviation principle for matrix models and their quantized versions, by tilting the measures using the asymptotics of spherical integrals obtained by Guionnet and Zeitouni. As examples, we obtain
  
==Thursday, February 10, [http://www.math.toronto.edu/cms/bloemendal-alex/ Alex Bloemendal (Toronto)]==
+
1) the large deviation principle for the empirical distribution of the diagonal entries of $UB_NU^*$, for a sequence of $N\times N$ diagonal matrices $B_N$ and unitary/orthogonal Haar distributed matrices $U$;
:Title: '''Finite rank perturbations of large random matrices
 
'''
 
  
:Abstract: Finite (or fixed) rank perturbations of large random matrices arise in a number of applications. The main phenomenon is a phase transition in the largest eigenvalues as a function of the strength of the perturbation. I will describe joint work with Bálint Virág in which we introduce a new way to study these models. The starting point is a reduction to a natural band form; under the soft edge scaling, it converges to a souped-up version of the known continuum random Schrödinger operator on the half-line. We describe the near-critical fluctuations in several ways, solving a known open problem in the real case. One characterization also yields a new route to the Painlevé structure in the celebrated Tracy-Widom laws.
+
2) the large deviation upper bound for the empirical eigenvalue distribution of $A_N+UB_NU^*$, for two sequences of $N\times N$ diagonal matrices $A_N, B_N$, and their complementary lower bounds at "good" probability distributions;
  
==Thursday, February 24, [http://www.math.bme.hu/~balazs/ Márton Balázs  (Technical University Budapest)]==
+
3) the large deviation principle for the Kostka number $K_{\lambda_N \eta_N}$, for two sequences of partitions $\lambda_N, \eta_N$ with at most $N$ rows;
:Title: '''Modelling flocks and prices: jumping particles with an attractive interaction'''
 
  
:Abstract: I will introduce a model of a finite number of competing particles on R. Real-life phenomena that could be modeled this way includes the evolution of stocks in a market, or herding behavior of animals. Given a particle configuration, the center of mass of the particles is computed by simply averaging the particle locations. The evolution is a continuous time Markov jump process: given a configuration and thus the center of mass, each particle jumps with a rate that depends on the particle's relative position compared to the center of mass. Those left behind have a higher jump rate than those in front of the center of mass. When a jump of a particle occurs, the jump length is chosen independently of everything from a positive distribution. Hence we see that the dynamics tries to keep the particles together.
+
4) the large deviation upper bound for the Littlewood-Richardson coefficients $c_{\lambda_N \eta_N}^{\kappa_N}$, for three sequences of partitions $\lambda_N, \eta_N, \kappa_N$ with at most $N$ rows, and their complementary lower bounds at "good" probability distributions.
  
:The main point of interest is the behavior of the model as the number of particles goes to infinity. We first heuristically wrote up a differential equation on the evolution of particle density. I will explain the heuristics, and show traveling wave solutions in a few cases. I will also present a surprising connection to extreme value statistics. Then I will briefly sketch a hydrodynamic argument which proves that the evolution of the system indeed converges to that governed by the differential equation.
+
This is a joint work with Belinschi and Guionnet.
  
:(Joint work with Miklós Rácz and Bálint Tóth)
+
== March 12, 2020, No seminar ==
 +
''' '''
  
==Wednesday, March 2, 3:30PM, VV B115 [http://www.stats.ox.ac.uk/~hammond/ Alan Hammond  (Oxford)]==
+
== March 19, 2020, Spring break ==
<span style="color:#FF0000">'''UNUSUAL TIME AND PLACE'''<span style="color:#009000">
+
''' '''
:Title: '''The sharpness of the phase transition for speed for biased walk in supercritical percolation'''
 
  
:Abstract: I will discuss a joint work with Alex Fribergh in which we study the biased random walk on the infinite cluster of supercritical percolation. Fixing any $d \geq 2$ and supercritical parameter $p >p_c$, the model has a parameter $\lambda > 0$ for the degree of bias of the walker in a certain preferred direction (which is another parameter, in $S^{d-1}$). We prove that the model has a sharp phase transition, that is, that there exists a critical value $\lambda_c > 0$ of the bias such that the walk moves at positive speed if $lambda < \lambda_c$ and at zero speed if $\lambda > \lambda_c$. This means that a stronger preference for the walker to move in a given direction actually causes the walk to slow down. The reason for this effect is a trapping phenomenon, and, as I will explain, our result is intimately tied to understanding the random geometry of the local environment that is trapping the particle at late time in the case when motion is sub-ballistic.
+
== March 26, 2020, CANCELLED, [https://math.cornell.edu/philippe-sosoe Philippe Sosoe] (Cornell) ==
 +
''' '''
  
==Thursday, March 31, [http://www2.warwick.ac.uk/fac/sci/maths/people/staff/stefan_grosskinsky/ Stefan Grosskinsky  (Warwick)]==
+
== April 2, 2020, CANCELLED, [http://pages.cs.wisc.edu/~tl/ Tianyu Liu] (UW Madison)==
:Title: '''Zero-range condensation at criticality'''
+
''' '''
  
:Abstract: Zero-range processes with decreasing jump rates exhibit a condensation transition, where a positive fraction of all particles condenses on a single lattice site when the total density exceeds a critical value. We study the onset of condensation at criticality, and establish a law of large numbers for the excess mass fraction in the maximum, which turns out to jump from zero to a positive value. Our results also include distributional limits for the fluctuations of the maximum, changing from standard extreme value statistics to Gaussian when the density crosses the critical point, as well as for the fluctuations of the bulk, showing that the mass outside the maximum is distributed homogeneously. The rigorous limit theorems can be extended heuristically to understand finite size effects and metastable dynamics in applications, which is confirmed by simulation results.
+
== April 9, 2020, CANCELLED, [http://stanford.edu/~ajdunl2/ Alexander Dunlap] (Stanford) ==
:This is joint work with Ines Armendariz, Michalis Loulakis and Paul Chleboun.
+
''' '''
  
 +
== April 16, 2020, CANCELLED, [https://statistics.wharton.upenn.edu/profile/dingjian/ Jian Ding] (University of Pennsylvania) ==
 +
''' '''
  
==Wednesday, April 6, 3:30PM, B115 VV, [http://www.math.uiuc.edu/~r-sowers/ Richard Sowers  (University of Illinois at Urbana-Champaign)]==
+
== April 22-24, 2020, CANCELLED, [http://frg.int-prob.org/ FRG Integrable Probability] meeting ==
<span style="color:#FF0000">'''UNUSUAL TIME AND PLACE'''<span style="color:#009000">
 
:Title: '''Very Hard to Borrow Stocks'''
 
  
:Abstract: We take a look at a possible dynamics for very hard-to-borrow (i.e., bankrupt) stocks.  The dynamics are 2-dimensional, and stems from a model proposed by Avellaneda and Lipkin for hard-to-borrow stocks.  We motivate and understand the model.  We
+
3-day event in Van Vleck 911
understand how to calibrate it and how to price puts on the stocks. 
 
  
:This is work in progress with Xiao Li and Mike Lipkin.
+
== April 23, 2020, CANCELLED, [http://www.hairer.org/ Martin Hairer] (Imperial College) ==
  
==Thursday, April 14, [http://euclid.colorado.edu/~englandj/MyBoulderPage.html Janos Englander  (University of Colorado - Boulder)]==
+
[https://www.math.wisc.edu/wiki/index.php/Colloquia Wolfgang Wasow Lecture] at 4pm in Van Vleck 911
:Title: '''TBA'''
 
  
:Abstract: TBA
+
== April 30, 2020, CANCELLED, [http://willperkins.org/ Will Perkins] (University of Illinois at Chicago) ==
 +
''' '''
  
==Thursday, April 21, [http://www.math.wisc.edu/~georgiou/index.html Nicos Georgiu (University of Wisconsin - Madison)]==
 
:Title: '''TBA'''
 
  
:Abstract: TBA
 
  
  
==Thursday, April 28, [http://www.stat.psu.edu/~fricks/ John Fricks  (Penn State)]==
 
:Title: '''TBA'''
 
  
:Abstract: TBA
 
  
  
==Thursday, May 5, [http://www.math.washington.edu/~soumik/ Soumik Pal  (University of Washington)]==
 
:Title: '''TBA'''
 
  
:Abstract: TBA
+
[[Past Seminars]]

Latest revision as of 17:18, 12 August 2020


Spring 2020

Thursdays in 901 Van Vleck Hall at 2:30 PM, unless otherwise noted. We usually end for questions at 3:20 PM.

If you would like to sign up for the email list to receive seminar announcements then please send an email to join-probsem@lists.wisc.edu


January 23, 2020, Timo Seppalainen (UW Madison)

Non-existence of bi-infinite geodesics in the exponential corner growth model

Whether bi-infinite geodesics exist has been a significant open problem in first- and last-passage percolation since the mid-80s. A non-existence proof in the case of directed planar last-passage percolation with exponential weights was posted by Basu, Hoffman and Sly in November 2018. Their proof utilizes estimates from integrable probability. This talk describes an independent proof completed 10 months later that relies on couplings, coarse graining, and control of geodesics through planarity and increment-stationary last-passage percolation. Joint work with Marton Balazs and Ofer Busani (Bristol).

January 30, 2020, Scott Smith (UW Madison)

Quasi-linear parabolic equations with singular forcing

The classical solution theory for stochastic ODE's is centered around Ito's stochastic integral. By intertwining ideas from analysis and probability, this approach extends to many PDE's, a canonical example being multiplicative stochastic heat equations driven by space-time white noise. In both the ODE and PDE settings, the solution theory is beyond the scope of classical deterministic theory because of the ambiguity in multiplying a function with a white noise. The theory of rough paths and regularity structures provides a more quantitative understanding of this difficulty, leading to a more refined solution theory which efficiently divides the analytic and probabilistic aspects of the problem, and remarkably, even has an algebraic component.

In this talk, we will discuss a new application of these ideas to stochastic heat equations where the strength of the diffusion is not constant but random, as it depends locally on the solution. These are known as quasi-linear equations. Our main result yields the deterministic side of a solution theory for these PDE's, modulo a suitable renormalization. Along the way, we identify a formally infinite series expansion of the solution which guides our analysis, reveals a nice algebraic structure, and encodes the counter-terms in the PDE. This is joint work with Felix Otto, Jonas Sauer, and Hendrik Weber.

February 6, 2020, Cheuk-Yin Lee (Michigan State)

Sample path properties of stochastic partial differential equations: modulus of continuity and multiple points

In this talk, we will discuss sample path properties of stochastic partial differential equations (SPDEs). We will present a sharp regularity result for the stochastic wave equation driven by an additive Gaussian noise that is white in time and colored in space. We prove the exact modulus of continuity via the property of local nondeterminism. We will also discuss the existence problem for multiple points (or self-intersections) of the sample paths of SPDEs. Our result shows that multiple points do not exist in the critical dimension for a large class of Gaussian random fields including the solution of a linear system of stochastic heat or wave equations.

February 13, 2020, Jelena Diakonikolas (UW Madison)

Langevin Monte Carlo Without Smoothness

Langevin Monte Carlo (LMC) is an iterative algorithm used to generate samples from a distribution that is known only up to a normalizing constant. The nonasymptotic dependence of its mixing time on the dimension and target accuracy is understood mainly in the setting of smooth (gradient-Lipschitz) log-densities, a serious limitation for applications in machine learning. We remove this limitation by providing polynomial-time convergence guarantees for a variant of LMC in the setting of non-smooth log-concave distributions. At a high level, our results follow by leveraging the implicit smoothing of the log-density that comes from a small Gaussian perturbation that we add to the iterates of the algorithm and while controlling the bias and variance that are induced by this perturbation. Based on joint work with Niladri Chatterji, Michael I. Jordan, and Peter L. Bartlett.

February 20, 2020, Philip Matchett Wood (UC Berkeley)

A replacement principle for perturbations of non-normal matrices

There are certain non-normal matrices whose eigenvalues can change dramatically when a small perturbation is added. However, when that perturbation is an iid random matrix, it appears that the eigenvalues become stable after perturbation and only change slightly when further small perturbations are added. Much of the work is this situation has focused on iid random gaussian perturbations. In this talk, we will discuss work on a universality result that allows for consideration of non-gaussian perturbations, and that shows that all perturbations satisfying certain conditions will produce the same limiting eigenvalue measure. Interestingly, this even allows for deterministic perturbations to be considered. Joint work with Sean O'Rourke.

February 27, 2020, No seminar

March 5, 2020, Jiaoyang Huang (IAS)

Large Deviation Principles via Spherical Integrals

In this talk, I'll explain a framework to study the large deviation principle for matrix models and their quantized versions, by tilting the measures using the asymptotics of spherical integrals obtained by Guionnet and Zeitouni. As examples, we obtain

1) the large deviation principle for the empirical distribution of the diagonal entries of $UB_NU^*$, for a sequence of $N\times N$ diagonal matrices $B_N$ and unitary/orthogonal Haar distributed matrices $U$;

2) the large deviation upper bound for the empirical eigenvalue distribution of $A_N+UB_NU^*$, for two sequences of $N\times N$ diagonal matrices $A_N, B_N$, and their complementary lower bounds at "good" probability distributions;

3) the large deviation principle for the Kostka number $K_{\lambda_N \eta_N}$, for two sequences of partitions $\lambda_N, \eta_N$ with at most $N$ rows;

4) the large deviation upper bound for the Littlewood-Richardson coefficients $c_{\lambda_N \eta_N}^{\kappa_N}$, for three sequences of partitions $\lambda_N, \eta_N, \kappa_N$ with at most $N$ rows, and their complementary lower bounds at "good" probability distributions.

This is a joint work with Belinschi and Guionnet.

March 12, 2020, No seminar

March 19, 2020, Spring break

March 26, 2020, CANCELLED, Philippe Sosoe (Cornell)

April 2, 2020, CANCELLED, Tianyu Liu (UW Madison)

April 9, 2020, CANCELLED, Alexander Dunlap (Stanford)

April 16, 2020, CANCELLED, Jian Ding (University of Pennsylvania)

April 22-24, 2020, CANCELLED, FRG Integrable Probability meeting

3-day event in Van Vleck 911

April 23, 2020, CANCELLED, Martin Hairer (Imperial College)

Wolfgang Wasow Lecture at 4pm in Van Vleck 911

April 30, 2020, CANCELLED, Will Perkins (University of Illinois at Chicago)





Past Seminars