### 10th World Congress in Probability and Statistics

## IMS Medallion Lecture (Daniela Witten)

### Selective inference for trees

Daniela Witten (University of Washington)

###### Session Chair

Ja-Yong Koo (Korea University)

## IMS Medallion Lecture (Andrea Montanari)

### High-dimensional interpolators: From linear regression to neural tangent models

Andrea Montanari (Stanford University)

[Based on joint papers with: Michael Celentano, Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Feng Ruan, Youngtak Sohn, Jun Yan, Yiqiao Zhong]

###### Session Chair

Myunghee Cho Paik (Seoul National University)

## IMS Lawrence D. Brown Ph.D. Student Award Session (Organizer: Institute of Mathematical Statistics)

### Efficient manifold approximation with spherelets

Didong Li (Princeton University / University of California)

### Toward instance-optimal reinforcement learning

Ashwin Pananjady (Georgia Institute of Technology)

### Bayesian pyramids: identifying interpretable discrete latent structures from discrete data

Yuqi Gu (Columbia University)

### Q&A for Invited Session 38

###### Session Chair

Tracy Ke (Harvard University)

## Random Growth, Spatial Processes and Related Models (Organizer: Erik Bates)

### Holes in first-passage percolation

Wai-Kit Lam (University of Minnesota)

### Coalescence estimates for the corner growth model with exponential weights

Xiao Shen (University of Wisconsin-Madison)

### Scaling limits of sandpiles

Ahmed Bou-Rabee (University of Chicago)

### Q&A for Organized Contributed Session 11

###### Session Chair

Erik Bates (University of California Berkeley)

## Recent Advances in Complex Data Analysis (Organizer: Seung Jun Shin)

### Kernel density estimation and deconvolution under radial symmetry

Kwan-Young Bak (Korea University)

### Penalized poly gram regression for bivariate smoothing

Jae-Hwan Jhong (Chungbuk National University)

### Penalized logistic regression using functional connectivity as covariates with an application to mild cognitive impairment

Eunjee Lee (Chungnam National University)

### Resmax: detecting voice spoofing attacks with residual network and max filter map

Il-Youp Kwak (Chung-Ang University)

### Weighted validation of heteroscedastic regression models for better selection

Yoonsuh Jung (Korea University)

### Q&A for Organized Contributed Session 19

###### Session Chair

Seung Jun Shin (Korea University)

## Recent Advances in Biostatistics (Organizer: Sangwook Kang)

### Bayesian nonparametric adjustment of confounding

Chanmin Kim (SungKyunKwan University)

### Multivariate point process models for microbiome image analysis

Kyu Ha Lee (Harvard University)

### Look before you leap: systematic evaluation of tree-based statistical methods in subgroup identification

Xiaojing Wang (University of Connecticut)

### Q&A for Organized Contributed Session 25

###### Session Chair

Sangwook Kang (Yonsei Univesity)

## BOK Contributed Session: Finance and Contemporary Issues (Organizer: BOK Economic Statistics Department)

### Multi-step reflection principle and barrier options

Seongjoo Song (Korea University)

### Change point analysis in Bitcoin return series: a robust approach

Junmo Song (Kyungpook National University)

### A self-normalization test for correlation matrix change

Ji Eun Choi (Pukyong National University)

### Volatility as a risk measure of financial time series : high frequency and realized volatility

Sun Young Hwang (Sookmyung Women's University)

### Q&A for Organized Contributed Session 31

###### Session Chair

Changryoung Baek (Sungkyunkwan University)

## Poster Session III-1

### A penalized matrix normal mixture model for clustering matrix data

Jinwon Heo (Chonnam National University)

### Univariate and multivariate normality tests using an entropy-based transformation

Shahzad Munir (Xiamen University)

### Geum river network data analysis via weighted PCA

Seeun Park (Seoul National University)

### Cauchy combination test with thresholding under arbitrary dependency structures

Junsik Kim (Seoul National University)

### Control charts for monitoring linear profiles in the detection of network intrusion

Daeun Kim (Dankook University)

### Benefits of international agreements as switching diffusions

Sheikh Shahnawaz (California State University)

### Estimation of Hilbertian varying coefficient models

Hyerim Hong (Seoul National University)

### Duality for a class of continuous-time reversible Markov models

Freddy Palma (Fundación Universidad de las Américas Puebla)

## Blackwell Lecture (Gabor Lugosi)

### Estimating the mean of a random vector

Gabor Lugosi (ICREA & Pompeu Fabra Universit)

###### Session Chair

Byeong Uk Park (Seoul National University)

## Tukey Lecture (Sara van de Geer)

### Max-margin classification and other interpolation methods

Sara van de Geer (Swiss Federal Institute of Technology Zürich)

This is joint work with Geoffrey Chinot, Felix Kuchelmeister and Matthias Löffler.

References

T. Liang and P. Sur. A precise high-dimensional asymptotic theory for boosting and minimum-$\ell_1$-norm interpolated classifiers, 2020. arXiv:2002.01586.

Y. Plan and R. Vershynin. One-bit compressed sensing by linear programming. Communications on Pure and Applied Mathematics, 66(8):1275–1297, 2013.

J. Tukey. Analyzing data: Sanctification or detective work? American Psychologist, 24:83–91, 1969.

P. Wojtaszczyk. Stability and instance optimality for gaussian measurements in compressed sensing. Foundations of Computational Mathematics, 10(1): 1–13, 2010.

###### Session Chair

Adam Jakubowski (Nicolaus Copernicus University)

## Quantum Statistics (Organizer: Cristina Butucea)

### Estimation of quantum state and quantum channel

Masahito Hayashi (Southern University of Science and Technology)

### Information geometry and local asymptotic normality for quantum Markov processes

Madalin Guta (University of Nottingham)

### Optimal adaptive strategies for sequential quantum hypothesis testing

Marco Tomamichel (National University of Singapore)

### Q&A for Invited Session 09

###### Session Chair

Cristina Butucea (École nationale de la statistique et de l'administration économique Paris)

## Random Trees (Organizer: Anita Winter)

### 1d Brownian loop soup, Fleming-Viot processes and Bass-Burdzy flow

Elie Aidekon (Fudan University)

Joint work with Yueyun Hu and Zhan Shi.

### A new state space of algebraic measure trees for stochastic processes

Wolfgang Löhr (University of Duisburg-Essen)

### Scaling Limits of critical rank-1 inhomogeneous random graphs

Minmin Wang (University of Sussex)

### Q&A for Invited Session 22

###### Session Chair

Anita Winter (University of Duisburg-Essen)

## High Dimensional Data Inference (Organizer: Florentina Bunea)

### Minimax rates for derivative-free stochastic optimization with higher order smooth objectives

Alexandre Tsybakov (Center for Research in Economics and Statistics (CREST))

The talk is based on a joint work with Arya Akhavan and Massimiliano Pontil.

### High-dimensional, multiscale online changepoint detection

Richard Samworth (University of Cambridge)

### Optimal transport and inference for stationary processes

Andrew Nobel (The University of North Carolina at Chapel Hill)

### Q&A for Invited Session 29

###### Session Chair

Florentina Bunea (Cornell University)

## Random Walks on Random Media (Organizer: Alexander Drewitz)

### Random walk on a barely supercritical branching random walk

Jan Nagel (Technische Universität Dortmund)

### Universality of cutoff for graphs with an added random matching

Perla Sousi (Cambridge University)

### Invariance principle for a random walk among a Poisson field of moving traps

Rongfeng Sun (National University of Singapore)

Joint work with S. Athreya and A. Drewitz.

### Q&A for Invited Session 34

###### Session Chair

Alexander Drewitz (Universität zu Köln)

## Bernoulli Society New Researcher Award Session (Organizer: Bernoulli Society)

### Hydrodynamic large deviations of strongly asymmetric interacting particle systems

Li-Cheng Tsai (Rutgers University)

### Conformal loop ensembles on Liouville quantum gravity with marked points

Nina Holden (Swiss Federal Institute of Technology Zürich)

### Integrability of Schramm-Loewner evolution and Liouville quantum gravity

Xin Sun (University of Pennsylvania)

### Q&A for Invited Session 37

###### Session Chair

Imma Curato (Ulm University)

## Rough Path Theory (Organizer: Ilya Chevyrev)

### Rough path theory and the stochastic Loewner equation

Vlad Margarint (New York University Shanghai)

The first part is based on joint work with Dmitry Belyaev, Terry Lyons, and the second part on a collaboration with James Foster.

### Rough path with jumps and its application in homogenization

Huilin Zhang (Fudan University)

This talk is based on works with Chevyrev, Friz, Korepanov and Melbourne.

### Probabilistic rough paths

William Salkeld (Universite Cote d'Azur)

This talk is based on preprints and ongoing work with my supervisor Francois Delarue at Universite Cote d'Azur.

### Transport and continuity equations with (very) rough noise

Nikolas Tapia (Weierstrass Institute / Technische Universität Berlin)

### Rough walks in random environment

Tal Orenshtein (Technische Universität Berlin, Weierstrass Institute for Applied Analysis and Stochastics)

Based on joint works with Olga Lopusanschi, with Jean-Dominique Deuschel and Nicolas Perkowski and with Johaness Bäumler, Noam Berger and Martin Slowik.

### Q&A for Organized Contributed Session 08

###### Session Chair

Ilya Chevyrev (University of Oxford)

## Recent Advances in Statistics (Organizer: Yunjin Choi)

### Identifiability of additive noise models using conditional variances

Gunwoong Park (University of Seoul)

### Multivariate functional group sparse regression: functional predictor selection

Jun Song (University of North Carolina at Charlotte)

### Causal foundations for fair and responsible machine learning

Joshua Loftus (London School of Economics)

### Network change point detection

Yi Yu (University of Warwick)

### Q&A for Organized Contributed Session 21

###### Session Chair

Yunjin Choi (University of Seoul)

## Topics Related to RMT

### On eigenvalue distributions of large auto-covariance matrices

Wangjun Yuan (The University of Hong Kong)

[1] Arup Bose and Walid Hachem, Smallest singular value and limit eigenvalue distribution of a class of non-Hermitian random matrices with statistical application, J. Multivariate Anal. 2020.

[2] Jianfeng Yao and Wangjun Yuan, On eigenvalue distributions of large auto-covariance, arXiv:2011.09165.

### Linear spectral statistics of sequential sample covariance matrices

Nina Dörnemann (Ruhr University Bochum)

### Couplings for Andersen dynamics and related piecewise deterministic Markov processes

Nawaf Bou-Rabee (Rutgers University Camden)

### Q&A for Contributed Session 09

###### Session Chair

Kyeongsik Nam (University of California at Los Angeles)

## Topics Related to KPZ Universality

### Upper tail decay of KPZ models with Brownian initial conditions

Balint Veto (Budapest University of Technology and Economics)

### Bijective matching between q-Whittaker and periodic Schur measures

Matteo Mucciconi (Tokyo Institute of Technology)

The talk is based on collaborations with Takashi Imamura and Tomohiro Sasamoto. Motivations and general ideas of our work are addressed by T. Imamura and applications to probabilistic systems are explained by T. Sasamoto.

### A new approach to KPZ models by determinantal and Pfaffian measures

Tomohiro Sasamoto (Tokyo Institute of Technology)

The talk is based on collaborations with Takashi Imamura and Matteo Mucciconi. Motivations and general ideas of our work are addressed by T. Imamura and the bijective proofs of identities are explained by M. Mucciconi.

### Q&A for Contributed Session 11

###### Session Chair

Jaehoon Kang (Korea Advanced Institute of Science and Technology (KAIST))

## Dimension Reduction and Model Selection

### Probabilistic principal curves on Riemannian manifolds

Seungwoo Kang (Seoul National University)

### The elastic information criterion for multicollinearity detection

Kimon Ntotsis (University of the Aegean)

### A bidimensional shock model driven by the space-fractional Poisson process

Alessandra Meoli (Università degli Studi di Salerno)

### Q&A for Contributed Session 21

###### Session Chair

Jisu Kim (Inria Saclay)

## Financial Data Analysis

### Hedging portfolio for a degenerate market model

Ihsan Demirel (Koç University)

### An optimal combination of proportional - excess of loss reinsurance with random premiums

Suci Sari (Statistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung)

### A novel inventory policy for imperfect items with stock dependent demand rate

Praveen V. P. (University of Calicut)

### Q&A for Contributed Session 35

###### Session Chair

Jae Youn Ahn (Ewha Womans University)

## Analysis of Dependent Data (Organizer: Chae Young Lim)

### Statistical learning with spatially dependent high-dimensional data

Taps Maiti (Michigan State University)

### Large-scale spatial data science with ExaGeoStat

Marc Genton (King Abdullah University of Science and Technology (KAUST))

### Multivariate spatio-temporal Hawkes process models of terrorism

Mikyoung Jun (University of Houston)

This is joint work with Scott Cook.

### Q&A for Invited Session 11

###### Session Chair

Chae Young Lim (Seoul National University)

## Randomized Algorithms (Organizer: Devdatt Dubhashi)

### Is your distribution in shape?

Ronitt Rubinfeld (Massachusetts Institute of Technology)

*monotone*if for any two comparableelements $x < y$ in the domain, we have that $p(x) < p(y)$. For example, for the classic $n$-dimensional hypercube domain, in which domain elements are described via $n$ different features, monotonicity implies that for every element, an increase in the value of one of the features can only increase its probability. We recount the development over the past nearly two decades of {\em monotonicity testing} algorithms for distributions over various discrete domains, which make no a priori assumptions on the underlying distribution. We study the sample complexity for testing whether a distribution is monotone as a function of the size of the domain, which can vary dramatically depending on the structure of the underlying domain. Not surprisingly, the sample complexity over high dimensional domains can be much greater than over low dimensional domains of the same size. Nevertheless, for many important domain structures, including high dimensional domains, the sample complexity is sublinear in the size of the domain. In contrast, when no a priori assumptions are made about the distribution, learning the distribution requires sample complexity that is linear in the size of the domain.The techniques used draw tools from a wide spectrum of areas, including statistics, optimization, combinatorics, and computational complexity theory.

### Beyond independent rounding: strongly Rayleigh distributions and traveling salesperson problem

Shayan Oveis Gharan (University of Washington)

### A survey of dependent randomized rounding

Aravind Srinivasan (University of Maryland, College Park)

### Q&A for Invited Session 19

###### Session Chair

Devdatt Dubhashi (Chalmers University)

## Stochastic Partial Differential Equations (Organizer: Leonid Mytnik)

### Phase analysis for a family of stochastic reaction-diffusion equations

Carl Mueller (University of Rochester)

### Regularization by noise for SPDEs and SDEs: a stochastic sewing approach

Oleg Butkovsky (Weierstrass Institute)

### Stochastic quantization, large N, and mean field limit

Hao Shen (University of Wisconsin-Madison)

(Joint work with Scott Smith, Rongchan Zhu and Xiangchan Zhu.)

### Q&A for Invited Session 23

###### Session Chair

Leonid Mytnik (Israel Institute of Technology)

## Pathwise Stochastic Analysis (Organizer: Hendrik Weber)

### Sig-Wasserstein Generative models to generate realistic synthetic time series

Hao Ni (University College London)

This is the joint work with Lukasz Szpruch (Uni of Edinburgh), Magnus Wiese (Uni of Kaiserslautern), Shujian Liao (UCL), Baoren Xiao (UCL).

### State space for the 3D stochastic quantisation equation of Yang-Mills

Ilya Chevyrev (University of Edinburgh)

Based on a joint work in progress with Ajay Chandra, Martin Hairer, and Hao Shen.

### A priori bounds for quasi-linear parabolic equations in the full sub-critical regime

Scott Smith (Chinese Academy of Sciences)

### Q&A for Invited Session 26

###### Session Chair

Hendrik Weber (University of Bath)

## Random Conformal Geometry and Related Fields (Organizer: Nam-Gyu Kang)

### Loewner dynamics for the multiple SLE(0) process

Tom Alberts (The University of Utah)

### Conformal field theory for annulus SLE

Sung-Soo Byun (Seoul National University)

### Convergence of martingale observables in the massive FK-Ising model

S. C. Park (Korea Institute of Advanced Study)

### Boundary Minkowski content of multi-force-point SLE$_\kappa(\underline\rho)$ curves

Dapeng Zhan (Michigan State University)

### Q&A for Organized Contributed Session 10

###### Session Chair

Nam-Gyu Kang (Korea Institute for Advanced Study)

## Stochastic Adaptive Optimization Algorithms and their Applications to Neural Networks (Organizer: Miklos Rasonyi & Sotirios Sabanis)

### An adaptive strong order 1 method for SDEs with discontinuous drift coefficient

Larisa Yaroslavtseva (University of Passau)

The talk is based on joint work with Thomas Müller-Gronbach (University of Passau).

References

[1]. T. Müller-Gronbach, L. Yaroslavtseva. Sharp lower error bounds for strong approximation of SDEs with discontinuous drift coefficient by coupling of noise. arXiv:2010.00915.

### Nonconvex optimization via TUSLA with discontinuous updating

Ying Zhang (Nanyang Technological University)

### Approximation of stochastic equations with irregular drifts

Konstantinos Dareiotis (University of Leeds)

This talk is based on joint works with Oleg Butkovsky, Khoa Lê, and Máté Gerencsér.

### Neural SDEs: deep generative models in the diffusion limit

Maxim Raginsky (University of Illinois at Urbana-Champaign)

### Diffusion approximations and control variates for MCMC

Eric Moulines (Ecole Polytechnique)

### Q&A for Organized Contributed Session 30

###### Session Chair

Sotirios Sabanis (University of Edinburgh)

## Stochastic Processes and Related Topics

### Parameter estimation for weakly interacting particle systems and stochastic McKean-Vlasov processes

Louis Sharrock (Imperial College London)

### CLT for cyclic long-memory processes

Andriy Olenko (La Trobe University)

This presentation is based on recent joint results in [2] with A.Ayache, M.Fradon (University of Lille, France) and R. Nanayakkara (La Trobe University, Australia).

[1] Alomari, H.M., Ayache, A., Fradon, M., Olenko, A. Estimation of cyclic long-memory parameters. Scand. J. Statist., 47, 1, 2020, 104-133.

[2] Ayache, A., Fradon, M., Nanayakkara, R., Olenko, A. Asymptotic normality of simultaneous estimators of cyclic long-memory processes. submitted, 1-30, https://arxiv.org/abs/2011.06229.

### Q&A for Contributed Session 04

###### Session Chair

Yeonwoo Rho (Michigan Technology University)

## Various Limit Theorems

### Limit theorems for non-stationary strongly mixing random fields

Cristina Tone (University of Louisville)

### On the law of the iterated logarithm and strong invariance principles in stochastic geometry

Johannes Krebs (Heidelberg University)

### Functional limit theorems for U-statistics

Mikolaj Kasprzak (University of Luxembourg)

### Proving Liggett's FCLT via Stein's method

Wasamon Jantai (Oregon State University)

### Q&A for Contributed Session 17

###### Session Chair

Chi Tim Ng (Hang Seng University of Hong Kong)

## Statistical Modeling and Prediction

### An evolution of the beta regression for non-monotone relations

Gloria Gheno (Ronin Institute)

### Robust censored regression with l1-norm regularization

Jad Beyhum (ORSTAT, Katholieke Universiteit Leuven)

### SPLVC modal regression with error-prone linear covariate

Tao Wang (University of California, Riverside)