### 10th World Congress in Probability and Statistics

## IMS Medallion Lecture (Laurent Saloff-Coste)

### Gambler's ruin problems

Laurent Saloff-Coste (Cornell University)

For this lecture, our starting point is a fair game of this sort involving three players, A, B, and C, holding a total on N tokens. That's already quite interesting. More generally, I will discuss techniques that allow us to understand the behavior of certain finite Markov chains before the time the chain is absorbed at a given boundary. This is based on joint work with Persi Diaconis and Kelsey Houston-Edwards.

###### Session Chair

Qi-Man Shao (Chinese University of Hong Kong)

## IMS Medallion Lecture (Elchanan Mossel)

### Simplicity and complexity of belief-propagation

Elchanan Mossel (Massachusetts Institute of Technology)

###### Session Chair

Krzysztof Burdzy (University of Washington)

## Mathematical Population Genetics and Computational Statistics (Organizer: Paul Jenkins)

### Mapping genetic ancestors

Graham Coop (University of California at Davis)

*Arabidopsis thaliana*genomes sampled across a wide geographic extent. We detect a very high dispersal rate in the recent past, especially longitudinally, and use inferred ancestor locations to visualize many examples of recent long-distance dispersal and recent admixture events. We also use inferred ancestor locations to identify the origin and ancestry of the North American expansion, to depict alternative geographic ancestries stemming from multiple glacial refugia. Our method highlights the huge amount of largely untapped information about past dispersal events and population movements contained in genome-wide genealogies.

### Cellular point processes: quantifying cell signaling

Barbara Engelhardt (Princeton University)

### Fitting stochastic epidemic models to gene genealogies using linear noise approximation

Vladimir Minin (University of California, Irvine)

The second class of methods provides estimates of important epidemiological parameters, such as infection and removal/recovery rates, but ignores variation in the dynamics of infectious disease spread. The third class of methods is the most advantageous statistically, but relies on computationally intensive particle filtering techniques that limits its applications. We propose a Bayesian model that combines phylodynamic inference and stochastic epidemic models, and achieves computational tractability by using a linear noise approximation (LNA) --- a technique that allows us to approximate probability densities of stochastic epidemic model trajectories. LNA opens the door for using modern Markov chain Monte Carlo tools to approximate the joint posterior distribution of the disease transmission parameters and of high dimensional vectors describing unobserved changes in the stochastic epidemic model compartment sizes (e.g., numbers of infectious and susceptible individuals). We illustrate our new method by applying it to Ebola genealogies estimated using viral genetic data from the 2014 epidemic in Sierra Leone and Liberia.

### Q&A for Invited Session 04

###### Session Chair

Paul Jenkins (University of Warwick)

## Deep Learning (Organizer: Johannes Schmidt-Hieber)

### Dynamics and phase transitions in deep neural networks

Yasaman Bahri (Google Research)

### Theoretical understanding of adding noises to deep generative models

Yongdai Kim (Seoul National University)

### Adversarial examples in random deep networks

Peter Bartlett (University of California at Berkeley)

Joint work with Sébastien Bubeck and Yeshwanth Cherapanamjeri

### Q&A for Invited Session 18

###### Session Chair

Johannes Schmidt-Hieber (University of Twente)

## Anomalous Diffusions and Related Topics (Organizer: Zhen-Qing Chen)

### Lp-Kato class measures for symmetric Markov processes under heat kernel estimates

Kazuhiro Kuwae (Fukuoka University)

### Green function estimates and Boundary Harnack principles for non-local operators whose kernels degenerate at the boundary

Panki Kim (Seoul National University)

### Heat kernel upper bounds for symmetric Markov semigroups

Jian Wang (Fujian Normal University )

### Inverse local time of one-dimensional diffusions and its comparison theorem

Lidan Wang (Nankai University)

### Archimedes' principle for ideal gas

Krzysztof Burdzy (University of Washington)

Joint work with Jacek Malecki

### Q&A for Organized Contributed Session 07

###### Session Chair

Zhen-Qing Chen (University of Washington)

## The Advances in Time Series and Spatial Statistics (Organizer: Wei-Ying Wu)

### Interpretable, predictive spatio-temporal models via enhanced pairwise directions estimation

ShengLi Tzeng (National Sun Yat-sen University)

### Model selection with a nested spatial correlation structure

Chun-Shu Chen (National Central University)

### Consistent order selection for ARFIMA models

Kun Chen (Southwestern University of Finance and Economics)

### Whittle likelihood for irregularly spaced spatial data

Soutir Bandyopadhyay (Colorado School of Mines)

### Q&A for Organized Contributed Session 17

###### Session Chair

Wei-Ying Wu (National Dong Hwa University)

## Advanced Statistical Methods for Complex Data (Organizer: Jongho Im)

### On the verifiable identification condition in NMAR missing data analysis

Kosuke Morikawa (Osaka University and The University of Tokyo)

### Bayesian hierarchical spatial model for small-area estimation with non-ignorable nonresponses and its application to the NHANES dental caries data

Ick Hoon Jin (Yonsei University)

### Raking-based relabeling classification method for highly imbalanced data

Seunghwan Park (Kangwon National University)

### Imputation approach for outcome dependent sampling design

Jongho Im (Yonsei University)

nonparametrically estimated and then a Bayesian bootstrap method is used to generate imputed values. The proposed method employs Rubin's variance formula for variance estimation of imputation estimators. A limited simulation study shows that the proposed method performs well and is comparable to the previous methods.

### Q&A for Organized Contributed Session 24

###### Session Chair

Seung Hwan Park (Kangwon National University)

## Time Series Analysis II

### Robust Bayesian analysis of multivariate time series

Yixuan Liu (The University of Auckland)

### Posterior consistency for the spectral density of non-Gaussian stationary time series

Yifu Tang (The University of Auckland)

### ARMA models for zero inflated count time series

Vurukonda Sathish (Indian Institute of Technology Bombay)

### Time-series data clustering via thick pen transformation

Minji Kim (Seoul National University)

### Q&A for Contributed Session 25

###### Session Chair

Joungyoun Kim (Yonsei University)

## Poster Session I-1

### GMOTE: Gaussian-based minority oversampling technique for imbalanced classification adapting tail probability of outliers

Seung Jee Yang (Hanyang University)

### Exact inference for an exponential parameter under generalized progressive type II hybrid censored competing risk data

Subin Cho (Daegu University)

### Meta-analysis methods for multiple related markers: applications to microbiome studies with the results on multiple $\alpha$-diversity indices

Hyunwook Koh (The State University of New York, Korea)

### Estimation for a nonlinear regression model with non-zero mean errors and an application to a biomechanical model

Hojun You (Seoul National University)

### Neural network-based clustering for ischemic stroke patients

Su Hoon Choi (Chonnam National University)

### Principal component analysis of amplitude and phase variation in multivariate functional data

Soobin Kim (Seoul National University)

### Clustering non-stationary advanced metering infrastructure data

Donghyun Kang (Chung-Ang University)

## Levy Lecture (Massimiliano Gubinelli)

### A variational method for Euclidean quantum fields

Massimiliano Gubinelli (University of Bonn)

###### Session Chair

Martin Hairer (Imperial College London)

## Doob Lecture (Nicolas Curien)

### Parking on Cayley trees and Frozen Erdös-Rényi

Nicolas Curien (Paris-Saclay University)

Based on joint work with Alice Contat

###### Session Chair

Wendelin Werner (Swiss Federal Institute of Technology Zürich)

## Bootstrap for High-dimensional Data (Organizer: Kengo Kato)

### Inference for nonlinear inverse problems

Vladimir Spokoinyi (Weierstrass Institute for Applied Analysis and Stochastics and Humboldt University of Berlin)

### Change point analysis for high-dimensional data

Xiaohui Chen (University of Illinois at Urbana-Champaign)

### Bootstrap test for multi-scale lead-lag relationships in high-frequency data

Yuta Koike (University of Tokyo)

### Q&A for Invited Session 16

###### Session Chair

Kengo Kato (Cornell University)

## Random Matrices and Related Fields (Organizer: Manjunath Krishnapur)

### The scaling limit of the characteristic polynomial of a random matrix at the spectral edge

Elliot Paquette (McGill University)

### Strong asymptotics of planar orthogonal polynomials: Gaussian weight perturbed by finite number of point charges

Seung Yeop Lee (University of South Florida)

### Secular coefficients and the holomorphic multiplicative chaos

Joseph Najnudel (University of Bristol)

### Q&A for Invited Session 27

###### Session Chair

Ji Oon Lee (Korea Advanced Institute of Science and Technology (KAIST))

## Statistical Inference for Graphs and Networks (Organizer: Betsy Ogburn)

### A goodness-of-fit test for exponential random graphs

Gesine Reinert (University of Oxford)

This talk is based on joint work with Nathan Ross and with Wenkai Xu.

### Networks in the presence of informative community structure

Alexander Volfovsky (Duke University)

### Motif estimation via subgraph sampling: the fourth-moment phenomenon

Bhaswar Bhattacharya (University of Pennsylvania)

### Q&A for Invited Session 28

###### Session Chair

Betsy Ogburn (Johns Hopkins University)

## Information Theory and Concentration Inequalities (Organizer: Chandra Nair)

### Algorithmic optimal transport in Euclidean spaces

Salman Beigi (Institute for Research in Fundamental Sciences (IPM))

This talk is based on a joint work with Omid Etesami and Amin Gohari.

### Entropy bounds for discrete log-concave distributions

Sergey Bobkov (University of Minnesota)

The talk is based on a joint work with Arnaud Marsiglietti and James Melbourne.

### Entropy and convex geometry

Tomasz Tkocz (Carnegie Mellon University)

(Based mainly on joint works with Ball, Madiman, Melbourne, Nayar.)

### Q&A for Invited Session 31

###### Session Chair

Chandra Nair (Chinese University of Hong Kong)

## Recent Developments for Dependent Data (Organizer: Mikyoung Jun)

### DeepKriging: spatially dependent deep neural networks for spatial prediction

Ying Sun (King Abdullah University of Science and Technology (KAUST))

### A model-free subsampling method based on minimum energy criterion

Wenlin Dai (Renmin University of China)

### Global wind modeling with transformed Gaussian processes

Jaehong Jeong (Hanyang University)

### Threshold estimation for continuous three-phase polynomial regression models with constant mean in the middle regime

Chih-Hao Chang (National University of Kaohsiung)

### Q&A for Organized Contributed Session 12

###### Session Chair

Mikyoung Jun (University of Houston)

## Non-Euclidean Statistical Inference (Organizer: Young Kyung Lee)

### Functional linear regression model with randomly censored data: predicting conversion time to Alzheimer's disease

Seong Jun Yang (Jeonbuk National University)

### Deconvolution estimation on hyperspheres

Jeong Min Jeon (Katholieke Universiteit Leuven)

### Confidence band for persistent homology of KDEs

Jisu Kim (Inria)

### Analysis of chemical-gene bipartite network via a user-based collaborative filtering method incorporating chemical structure information

Namgil Lee (Kangwon National University)

### Q&A for Organized Contributed Session 16

###### Session Chair

Young Kyung Lee (Kangwon National University)

## Financial Mathematics and Probabilistic Modeling

### Solving the selection-recombination equation: ancestral lines and duality

Frederic Alberti (Bielefeld University)

We consider the case of an arbitrary number of neutral loci, linked to a single selected locus. In this setting, we investigate how the (random) genealogical structure of the problem can be succinctly encoded by a novel `ancestral initiation graph', and how it gives rise to a recursive integral representation of the solution with a clear, probabilistic interpretation.

References:

-F. Alberti and E. Baake, Solving the selection-recombination equation: Ancestral lines under selection and recombination, https://arxiv.org/abs/2003.06831

-F. Alberti, E. Baake and C. Herrmann, Selection, recombination, and the ancestral initiation graph, https://arxiv.org/abs/2101.10080

### Short time asymptotics for modulated rough stochastic volatility models

Barbara Pacchiarotti (Università degli studi di Roma "Tor Vergata")

### How to detect a salami slicer: a stochastic controller-stopper game with unknown competition

Kristoffer Lindensjö (Stockholm University)

### Q&A for Contributed Session 02

###### Session Chair

Hyungbin Park (Seoul National University)

## SDEs and Fractional Brownian Motions

### Weak rough-path type solutions for singular Lévy SDEs

Helena Katharina Kremp (Freie Universität Berlin)

### Functional limit theorems for approximating irregular SDEs, general diffusions and their exit times

Mikhail Urusov (University of Duisburg-Essen)

(1) A functional limit theorem (FLT) for weak approximation of the paths of arbitrary continuous Markov processes;

(2) An FLT for weak approximation of the paths and exit times.

The second FLT has a stronger conclusion but requires a stronger assumption, which is essential. We propose a new scheme, called EMCEL, which satisfies the assumption of the second FLT and thus allows to approximate every one-dimensional continuous Markov process together with its exit times. The approach is illustrated by a couple of examples with peculiar behavior, including an irregular SDE, for which the corresponding Euler scheme does not converge even weakly, a sticky Brownian motion and a Brownian motion slowed down on the Cantor set.

This is a joint work with Stefan Ankirchner and Thomas Kruse.

### Q&A for Contributed Session 07

###### Session Chair

Ildoo Kim (Korea University)

## Neural Networks and Deep Learning

### Simulated Annealing-Backpropagation Algorithm on Parallel Trained Maxout Networks (SABPMAX) in detecting credit card fraud

Sheila Mae Golingay (University of the Philippines-Diliman)

### The smoking gun: statistical theory improves neural network estimates

Sophie Langer (Technische Universität Darmstadt)

### Stochastic block model for multiple networks

Tabea Rebafka (Sorbonne Université)

### Deep neural networks for faster nonparametric regression models

Mehmet Ali Kaygusuz (The Middle East Technical University)

[1] Bauer, B and Kohler,M, “On deep learning as a remedy for the curse of dimensionality in nonparametric regression”, The Annals of Statistics, 47(4), 2019, 2261-2285.

[2] Efron,B, "Bootstrap methods: another look at the jackknife" the Annals of Statistics,7(1):1-26,1979

[3] Hamparsum Bozdogan. “Model selection and Akaike’s information criterion (AIC): The general theory and its analytical extensions”. In: Psychometrika 52.3 (1987), pp. 345–370.

[4] Sen,B, Banerjee, M and Woodroofe,M., “In-cosistency of bootstrap: The Grenander estimator ”, The Annals of Statistics,38(4),2010,1953-1977.

[5] Schmidt-Hieber, J., “Nonparametric regression using deep neural networks with ReLu activation function”, The Annals of Statistics, 48(4), 2020, 1875-1897.

### Generative model for fbm with deep ReLU neural networks

Michael Allouche (Ecole Polytechnique)

### Q&A for Contributed Session 28

###### Session Chair

Jong-June Jeon (University of Seoul)

## Poster Session I-2

### Geometrically Adapted Langevin Algorithm (GALA) for Markov Chain Monte Carlo (MCMC) simulations

Mariya Mamajiwala (University College London)

### Bayes estimation for the Weibull distribution under generalized adaptive hybrid progressive censored competing risks data

Yeongjae Seong (Daegu University)

### Large deviations of mean-field interacting particle systems in a fast varying environment

Sarath Yasodharan (Indian Institute of Science)

### Stochastic homogenisation of Gaussian fields

Leandro Chiarini (Utrecht University)

### Concentration inequality for U-statistics for uniformly ergodic Markov chains, and applications

Quentin Duchemin (Université Gustave Eiffel)

### A Bayesian illness-death model to approach the incidence of recurrent hip fracture and death in elderly patients

Fran Llopis-Cardona (Foundation for the Promotion of Health and Biomedical Research of Valencia Region (FISABIO))

### The contact process with two types of particles and priority: metastability and convergence in infinite volume

Mariela Pentón Machado (Instituto de Matemática e Estatística, Universidade de São Paulo)

### A nonparametric instrumental approach to endogeneity in competing risks models

Jad Beyhum (ORSTAT, Katholieke Universiteit Leuven)

## Scaling Limits of Disordered Systems and Disorder Relevance (Organizer: Rongfeng Sun)

### Exceptional geodesic pairs in the directed landscape

Erik Bates (University of Wisconsin-Madison)

This talk is based on joint work with Shirshendu Ganguly and Alan Hammond.

### Disorder relevance and the continuum random field Ising model

Adam Bowditch (University College Dublin)

### A CLT for KPZ on torus

Yu Gu (Carnegie Mellon University)

### Q&A for Invited Session 02

###### Session Chair

Rongfeng Sun (National University of Singapore)

## High-dimensional Robustness (Organizer: Stanislav Minsker)

### Distribution-free robust linear regression

Nikita Zhivotovskiy (Swiss Federal Institute of Technology Zürich)

### Algorithmic high-dimensional robust statistics

Ilias Diaconicolas (University of Wisconsin-Madison)

### Robust estimation of a mean vector with respect to any norm : a minimax MOM and a Stahel-Donoho Median of means estimators

Guillaume Lecué (Center for Research in Economics and Statistics (CREST))

### Q&A for Invited Session 07

###### Session Chair

Stanislav Minsker (University of Southern California)

## Functional Data Analysis (Organizer: Aurore Delaigle)

### Partially specified covariance operators and intrinsically functional graphical models

Victor Panaretos (École polytechnique fédérale de Lausanne)

Based on joint work with K. Waghmare (EPFL).

### Domain selection for functional linear models: a dynamic RKHS approach

Jane-Ling Wang (University of California at Davis)

### Simultaneous Inference for function-valued parameters: A fast and fair approach

Dominik Liebl (University of Bonn)

### Q&A for Invited Session 08

###### Session Chair

Yunjin Choi (University of Seoul)

## Statistical Learning (Organizer: Yichao Wu)

### Equivariant Variance Estimation for Multiple Change-point Model

Ning Hao (University of Arizona)

### A forward approach for sufficient dimension reduction in binary classification

Seung Jun Shin (Korea University)

### Variable Selection for Global Fréchet Regression

Danielle Tucker (University of Illinois at Chicago)

### Q&A for Invited Session 32

###### Session Chair

Yichao Wu (University of Illinois at Chicago)

## Bernoulli Paper Prize Session (Organizer: Bernoulli Society)

### Bernoulli Prize for an outstanding survey article in Probability: From infinite random matrices over finite fields to square ice

Leonid Petrov (University of Virginia)

(Chair: Ofer Zeitouni)

### Bernoulli Journal Read Paper Award: A general frequency domain method for assessing spatial covariance structures

Soutir Bandyopadhyay (Colorado School of Mines)

(Chair: Richard Samworth)

### Q&A for Invited Session 41

###### Session Chair

Ofer Zeitouni (Weizmann Institute of Science) / Richard Samworth (University of Cambridge)

## Theoretical Analysis of Random Walks, Random Graphs and Clustering (Organizer: Ji Oon Lee)

### Spectral large deviations for sparse random matrices

Kyeongsik Nam (University of California, Los Angeles)

### Robust hypergraph clustering via convex relaxation of truncated MLE

Hye Won Chung (Korea Advanced Institute of Science and Technology (KAIST))

### Convergence rate to the Tracy-Widom laws for the largest eigenvalue of Wigner matrices

Kevin Schnelli (KTH Royal Institute of Technology)

### Attributed graph alignment

Lele Wang (University of British Columbia)

This is joint work with Ning Zhang and Weina Wang.

### Minkowski content for the scaling limit of loop-erased random walk in three dimensions

Xinyi Li (Peking University)

### Q&A for Organized Contributed Session 06

###### Session Chair

Ji Oon Lee (Korea Advanced Institute of Science and Technology (KAIST))

## Recent Advances in Complex Time Series Analysis (Organizer: Haeran Cho)

### Change points detection for high dimensional time series

Likai Chen (Washington University in Saint Louis)

### Asymptotics of large autocovariance matrices

Monika Bhattacharjee (Indian Institute of Technology Bombay)

### Factor models for matrix-valued high-dimensional time series

Xialu Liu (San Diego State University)

### Multi-level changepoint inference for periodic data sequences

Anastasia Ushakova (Lancaster University)

### Q&A for Organized Contributed Session 13

###### Session Chair

Haeran Cho (University of Bristol)