### 10th World Congress in Probability and Statistics

## Laplace Lecture (Tony Cai)

### Transfer Learning: Optimality and adaptive algorithms

Tony Cai (University of Pennsylvania)

###### Session Chair

Runze Li (Pennsylvania State University)

## Public Lecture (Young-Han Kim)

### Structure and Randomness in Data

Young-Han Kim (University of California at San Diego and Gauss Labs Inc.)

Keywords: Information theory, noise, manufacturing, computer vision, distributed computing, probability laws.

###### Session Chair

Joong-Ho Won (Seoul National University)

## Recent Advances in Shape Constrained Inference (Organizer: Bodhisattva Sen)

### Global rates of convergence in mixture density estimation

Arlene Kyoung Hee Kim (Korea University)

### Convex regression in multidimensions

Adityanand Guntuboyina (University of California Berkeley)

This is joint work with Gil Kur, Frank Fuchang Gao and Bodhisattva Sen.

### Multiple isotonic regression: limit distribution theory and confidence intervals

Qiyang Han (Rutgers University)

In the second part of the talk, we demonstrate how to use this limiting distribution to construct tuning-free pointwise nonparametric confidence intervals in this model, despite the existence of an infinite-dimensional nuisance parameter in the limit distribution that involves multiple unknown partial derivatives of the true regression function. We show that this difficult nuisance parameter can be effectively eliminated by taking advantage of information beyond point estimates in the block max-min and min-max estimators through random weighting. Notably, the construction of the confidence intervals, even new in the univariate setting, requires no more efforts than performing an isotonic regression for once using the block max-min and min-max estimators, and can be easily adapted to other common monotone models.

This talk is based on joint work with Hang Deng and Cun-Hui Zhang.

### Q&A for Invited Session 05

###### Session Chair

Bodhisattva Sen (Columbia University)

## Optimization in Statistical Learning (Organizer: Garvesh Raskutti)

### Statistical inference on latent network growth processes using the PAPER model

Min Xu (Rutgers University)

### Adversarial classification, optimal transport, and geometric flows

Nicolas Garcia Trillos (University of Wisconsin-Madison)

### Capturing network effect via fused lasso penalty with application on shared-bike data

Yunjin Choi (University of Seoul)

### Q&A for Invited Session 06

###### Session Chair

Garvesh Raskutti (University of Wisconsin-Madison)

## Random Matrices and Infinite Particle Systems (Organizer: Hirofumi Osada)

### Dynamical universality for random matrices

Hirofumi Osada (Kyushu University)

[1] Hirofumi Osada, Hideki Tanemura, Infinite-dimensional stochastic differential equations and tail $\sigma$-fields, Probability Theory and Related Fields 177, 1137-1242 (2020).

[2] Yosuke Kawamoto, Hirofumi Osada, Hideki Tanemura, Uniqueness of Dirichlet forms related to infinite systems of interacting Brownian motions, (online) Potential Anal.

### Signal processing via the stochastic geometry of spectrogram level sets

Subhroshekhar Ghosh (National University of Singapore)

Based on joint work with Meixia Lin and Dongfang Sun.

### Logarithmic derivatives and local densities of point processes arising from random matrices

Shota Osada (Kyushu University)

[1] Hirofumi Osada, Infinite-dimensional stochastic differential equations related to random matrices, Probability theory and related fields, 2012, 153(3-4), 471--509.

[2] Alexander I Bufetov, Andrey V Dymov, Hirofumi Osada, The logarithmic derivative for point processes with equivalent Palm measures, J. Math. Soc. Japan, 71(2), 2019, 451--469.

[3] Hirofumi Osada, Hideki Tanemura, Infinite-dimensional stochastic differential equations and tail $\sigma$-fields, Probability Theory and Related Fields 177, 1137-1242 (2020).

### Stochastic differential equations for infinite particle systems of jump type with long range interactions

Hideki Tanemura (Keio university)

This talk is based on a collaboration with Shota Esaki (Fukuoka University).

### Q&A for Organized Contributed Session 09

###### Session Chair

Hirofumi Osada (Kyushu University)

## Advanced Learning Methods for Complex Data Analysis (Organizer: Xinlei Wang)

### Peel learning for pathway-related outcome prediction

Rui Feng (University of Pennsylvania)

### Principal boundary for data on manifolds

Zhigang Yao (National University of Singapore)

### Probabilistic semi-supervised learning via sparse graph structure learning

Li Wang (University of Texas at Arlington)

### Bayesian modeling for paired data in genome-wide association studies with application to breast cancer

Min Chen (University of Texas at Dallas)

### Q&A for Organized Contributed Session 18

###### Session Chair

Xinlei Wang (Southern Methodist University)

## Bayesian Inference for Complex Models (Organizer: Joungyoun Kim)

### Nonparametric Bayesian latent factor model for multivariate functional data with covariate dependency

Yeonseung Chung (Korea Advanced Institute of Science and Technology (KAIST))

### Bayesian model selection for ultrahigh-dimensional doubly-intractable distributions

Jaewoo Park (Yonsei University)

### Post-processed posteriors for banded covariances

Kwangmin Lee (Seoul National University)

### Adaptive Bayesian inference for current status data on a grid

Minwoo Chae (Pohang University of Science and Technology)

### Q&A for Organized Contributed Session 27

###### Session Chair

Joungyoun Kim (Yonsei Univesity)

## Recent advances in Time Series Analysis (Organizer: Changryoung Baek)

### Resampling long-range dependent time series

Shuyang Bai (University of Georgia)

### Robust test for structural instability in dynamic factor models

Changryong Baek (Sungkyunkwan University)

### On scaling in high dimensions

Gustavo Didier (Tulane University)

This is joint work with P. Abry (CNRS and ENS-Lyon), B.C. Boniece (Washington University in St Louis) and H. Wendt (CNRS and Université de Toulouse).

### Thresholding and graphical local Whittle estimation

Marie Duker (Cornell University)

### Cotrending: testing for common deterministic trends in varying means model

Vladas Pipiras (University of North Carolina at Chapel Hill)

### Q&A for Organized Contributed Session 28

###### Session Chair

Changryoung Baek (Sungkyunkwan University)

## Spatial Data Analysis

### Wild bootstrap for high-dimensional spatial data

Daisuke Kurisu (Tokyo Institute of Technology)

### Lifting scheme for streamflow data in river networks

Seoncheol Park (Chungbuk National University)

### Optimal designs for some bivariate cokriging models

Subhadra Dasgupta (Indian Institute of Technology Bambay-Monash Research Academy)

### Q&A for Contributed Session 29

###### Session Chair

Yaeji Lim (Chung-Ang University)

## Poster Session II-1

### Nonconstant error variance in generalized propensity score model

Doyoung Kim (Sungkyunkwan University)

### Causal mediation analysis with multiple mediators of general structures

Youngho Bae (Sungkyunkwan University)

### A fuzzy clustering ensemble based Mapper algorithm

SungJin Kang (Chung-Ang University)

Since Mapper algorithm can be applied to the clustering and feature selection with visualization, it is used in various fields such as biology, chemistry, etc. However, there are some resolution parameters to be chosen before applying the Mapper algorithm, and the results are sensitive to these selection. In this paper, we focus on the selection of the two resolution parameters, the number of intervals, and the overlapping percentage. We propose a new parameter selection method in Mapper based on ensemble technique. We generate multiple Mapper results under various parameters, and apply the fuzzy clustering ensemble method to combine the results. Three real data are considered to evaluate mapper algorithms including proposed one, and the results demonstrate the superiority of the proposed ensemble Mapper method.

### Analysis of the association between suicide attempts and meteorological factors

Seunghyeon Kim (Chonnam National University)

### Spectral clustering with the Wasserstein distance and its application

SangHun Jeong (Pusan National University)

### Robust covariance estimation for partially observed functional data

Hyunsung Kim (Chung-Ang University)

### Fast Bayesian functional regression for non-Gaussian spatial data

Yeo Jin Jung (Yonsei University)

## Wald Lecture 2 (Martin Barlow)

### Low dimensional random fractals

Martin Barlow (University of British Columbia)

(1) control of the size of balls (2) control of the resistance across annuli, and (3) a smoothness result (a Harnack inequality). In the ‘low dimensional case’ the Harnack inequality is not needed, and (2) can be replaced by easier bounds on the resistance between points. Many random fractals of interest are low dimensional: examples include critical branching processes, the incipient infinite cluster (IIC) for percolation in high dimensions, and the uniform spanning tree. Critical percolation in d=2 remains a challenge however.

###### Session Chair

Takashi Kumagai (Kyoto University)

## IMS Medallion Lecture (Gerard Ben Arous)

### Random determinants and the elastic manifold

Gerard Ben Arous (New York University)

This is joint work with Paul Bourgade and Benjamin McKenna (Courant Institute, NYU).

###### Session Chair

Arup Bose (Indian Statistical Institute)

## Conformal Invariance and Related Topics (Organizer: Hao Wu)

### Asymptotics of determinants of discrete Laplacians

Konstantin Izyurov (University of Helsinki)

### On Loewner evolutions with jumps

Eveliina Peltola (Rheinische Friedrich-Wilhelms-Universität Bonn)

Joint work with Anne Schreuder (Cambridge).

### Extremal distance and conformal radius of a CLE_4 loop

Titus Lupu (Centre National de la Recherche Scientifique / Sorbonne Université)

### Q&A for Invited Session 01

###### Session Chair

Hao Wu (Yau Mathematical Sciences Center, Tsinghua University)

## Optimal Transport (Organizer: Philippe Rigollet)

### Density estimation and conditional simulation using triangular transport

Youssef Marzouk (Massachusetts Institute of Technology)

### Estimation of Wasserstein distances in the spiked transport model

Jonathan Niles-Weed (Courant Institute of Mathematical Sciences, New York University)

### Statistical estimation of barycenters in metric spaces and the space of probability measures

Quentin Paris (National Research University Higher School of Economics)

### Q&A for Invited Session 14

###### Session Chair

Philippe Rigollet (Massachusetts Institute of Technology)

## Probabilistic Theory of Mean Field Games (Organizer: Xin Guo)

### Portfolio liquidation games with self-exciting order flow

Ulrich Horst (Humboldt University Berlin)

This is joint work with Guanxing Fu and Xiaonyu Xia.

### A mean-field game approach to equilibrium pricing in renewable energy certificate markets

Sebastian Jaimungal (University of Toronto)

### Entropic optimal transport

Marcel Nutz (Columbia University)

Based on joint works with Espen Bernton (Columbia), Promit Ghosal (MIT), Johannes Wiesel (Columbia).

###### Session Chair

Xin Guo (University of California, Berkeley)

## Stochastic Analysis in Mathematical Finance and Insurance (Organizer: Marie Kratz)

### From signature based models in finance to affine and polynomial processes and back

Christa Cuchiero (University of Vienna)

The talk is based on joint works with Guido Gazzani, Francesca Primavera, Sara-Svaluto-Ferro and Josef Teichmann.

### Optimal dividends with capital injections at a level-dependent cost

Ronnie Loeffen (University of Manchester)

This is joint work with Zbigniew Palmowski.

### Exponential Lévy-type change-point models in mathematical finance

Lioudmila Vostrikova (University of Angers)

### Q&A for Invited Session 35

###### Session Chair

Marie Kratz (ESSEC Business School, CREAR)

## KSS Invited Session: Nonparametric and Semi-parametric Approaches in Survival Analysis (Organizer: Woncheol Jang)

### Smoothed quantile regression for censored residual lifetime

Sangwook Kang (Yonsei University)

### Superefficient estimation of future conditional hazards based on marker information

Enno Mammen (Heidelberg University)

### On a semiparametric estimation method for AFT mixture cure models

Ingrid Van Keilegom (Katholieke Universiteit Leuven)

### Q&A for Invited Session 40

###### Session Chair

Woncheol Jang (Seoul National University)

## Gaussian Processes (Organizer: Naomi Feldheim)

### Gaussian determinantal processes: a new model for directionality in data

Subhro Ghosh (National University of Singapore)

Based on joint work with Philippe Rigollet.

### Persistence exponents of Gaussian stationary functions

Ohad Noy Feldheim (Hebrew University of Jerusalem)

Joint work with N. Feldheim and S. Mukherjee.

### Connectivity of the excursion sets of Gaussian fields with long-range correlations

Stephen Muirhead (University of Melbourne)

### Overcrowding estimates for the nodal volume of stationary Gaussian processes on R^d

Lakshmi Priya (Indian Institute of Science)

We study the unlikely event of overcrowding of the nodal set in [0,T]^d; this is the event that the volume of the nodal set in [0,T]^d is much larger than its expected value. Under some mild assumptions on the spectral measure, we obtain estimates for the overcrowding event's probability. We first get overcrowding estimates for the zero count of SGPs on R. In higher dimensions, we consider Crofton's formula which gives the volume of the nodal set in terms of the number of intersections of the nodal set with all lines in R^d. We discretise this formula to get a more workable version of it; we use this and the ideas used to obtain the overcrowding estimates in one dimension to get the overcrowding estimates in higher dimensions.

### Q&A for Organized Contributed Session 03

###### Session Chair

Naomi Feldheim (Bar-Ilan University)

## Theories and Applications for Complex Data Analysis (Organizer: Arlene K.H. Kim)

### Partly interval-censored rank regression

Sangbum Choi (Korea University)

### Two-sample testing of high-dimensional linear regression coefficients via complementary sketching

Tengyao Wang (University College London)

### Optimal rates for independence testing via U-statistic permutation tests

Tom Berrett (University of Warwick)

This is joint work with Ioannis Kontoyiannis and Richard Samworth.

### Empirical Bayes PCA in high dimensions

Zhou Fan (Yale University)

### Q&A for Organized Contributed Session 20

###### Session Chair

Arlene K.H. Kim (Korea University)

## Random Structures

### Universal phenomena for random constrained permutations

Jacopo Borga (University of Zurich)

### The scaling limit of the strongly connected components of a uniform directed graph with an i.i.d. degree sequence

Serte Donderwinkel (University of Oxford)

### Spherical principal curves

Jongmin Lee (Seoul National University)

### Q&A for Contributed Session 13

###### Session Chair

Namgyu Kang (Korea Institute for Advanced Study)

## Copula Modeling

### Estimation of multivariate generalized gamma convolutions through Laguerre expansions

Oskar Laverny (Université Lyon 1)

### Copula-based Markov zero-inflated count time series models

Mohammed Alqawba (Qassim University)

### Bi-factor and second-order copula models for item response data

Sayed H. Kadhem (University of East Anglia)

### Q&A for Contributed Session 20

###### Session Chair

Daewoo Pak (Yonsei University)

## Multivariate Data Analysis

### A nonparametric test for paired data

Grzegorz Wyłupek (Institute of Mathematics, University of Wrocław)

### Inference for Generalized Multivariate Analysis of Variance (GMANOVA) models, under multivariate skew t distribution for modelling skewed and heavy-tailed data

Sayantee Jana (Indian Institute of Management Nagpur)

### Multiscale representation of directional scattered data: use of anisotropic radial basis functions

Junhyeon Kwon (Seoul National Universtiy)

### Q&A for Contributed Session 26

###### Session Chair

Yunjin Choi (University of Seoul)

## Statistical Prediction

### Robust geodesic regression

Ha-Young Shin (Seoul National University)

### A multi-sigmoidal logistic model: statistical analysis and first-passage-time application

Paola Paraggio (Università degli Studi di Salerno (UNISA))

However, many real phenomena exhibit different phases, each one following a sigmoidal-type pattern. Stimulated by these more complex dynamics, many researchers investigate generalized versions of classical sigmoidal models characterized by several inflection points.

Along these research lines, a generalization of the classical logistic growth model is considered in the present work, introducing in its expression a polynomial term. The model is described by a stochastic differential equation obtained from the deterministic counterpart by adding a multiplicative noise term. The resulting diffusion process, having a multi-sigmoidal mean, may be useful in the description of particular growth dynamics in which the evolution occurs by stages.

The problem of finding the maximum likelihood estimates of the parameters involved in the definition of the process is also addressed. Precisely, the maximization of the likelihood function will be performed by means of meta-heuristic optimization techniques. Moreover, various strategies for the selection of the optimal degree of the polynomial will be provided.

Further, the first-passage-time (FPT) problem is considered: an approximation of its density function will be obtained numerically, by means of the fptdApprox R-package

Finally, some simulated examples are presented.

### Statistical inference for functional linear problems

Tim Kutta (Ruhr University Bochum)

### Q&A for Contributed Session 31

###### Session Chair

Changwon Lim (Chung-Ang University)

## Potential Theory for Non-local Operators and Jump Processes (Organizer: Panki Kim)

### SDEs driven by multiplicative stable-like Levy processes

Zhen-Qing Chen (University of Washington)

Based on joint work with Xicheng Zhang and Guohuan Zhao.

### Periodic homogenization of non-symmetric Lévy-type processes

Takashi Kumagai (Kyoto University)

### Optimal Hardy identities and inequalites for the fractional Laplacian on $L^p$

Krzysztof Bogdan (Wrocław University of Science and Technology)

### Q&A for Invited Session 03

###### Session Chair

Panki Kim (Seoul National University)

## Change-point Problems for Complex Data (Organizer: Claudia Kirch)

### Two-sample tests for relevant differences in the eigenfunctions of covariance operators

Alexander Aue (University of California at Davis)

### Multiple change point detection under serial dependence

Haeran Cho (University of Bristol)

### An asymptotic test for constancy of the variance in a time series

Herold Dehling (Ruhr-University Bochum)

### Q&A for Invited Session 10

###### Session Chair

Claudia Kirch (Otto von Guericke University Magdeburg)

## Statistics for Data with Geometric Structure (Organizer: Sungkyu Jung)

### Wasserstein regression

Hans-Georg Müller (University of California, Davis)

### Finite sample smeariness for Fréchet means

Stephan Huckemann (Georg-August-Universitaet Goettingen)

### Score matching for microbiome compositional data

Janice Scealy (Australian National University)

### Q&A for Invited Session 12

###### Session Chair

Sungkyu Jung (Seoul National University)

## Random Graphs (Organizer: Christina Goldschmidt)

### An unexpected phase transition for percolation on scale-free networks

Souvik Dhara (Massachusetts Institute of Technology)

Based on joint work with Shankar Bhamidi, Remco van der Hofstad.

### Recent results for the graph alignment problem

Marc Lelarge (INRIA)

### Local law and Tracy-Widom limit for sparse stochastic block models

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

### Q&A for Invited Session 25

###### Session Chair

Christina Goldschmidt (University of Oxford)

## Problems and Approaches in Multi-Armed Bandits (Organizer: Vianney Perchet)

### Dynamic pricing and learning under the Bass model

Shipra Agrawal (Columbia University)

### TensorPlan: A new, flexible, scalable and provably efficient local planner for huge MDPs

Csaba Szepesvari (Deepmind & University of Alberta)

### On the importance of (linear) structure in contextual multi-armed bandit

Alessandro Lazaric (Facebook AI Research)

Most relevant references:

T. Lattimore, Cs. Szepesvari. "The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits", 2016.

B. Hao, T. Lattimore, Cs. Szepesvari, "Adaptive Exploration in Linear Contextual Bandit", 2019.

A. Tirinzoni, M. Pirotta, M. Restelli, A. Lazaric, "An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits", 2020.

M. Papini, A. Tirinzoni, M. Restelli, A. Lazaric, M. Pirotta, "Leveraging Good Representations in Linear Contextual Bandits", 2021.

### Q&A for Invited Session 36

###### Session Chair

Vianney Perchet (École nationale de la statistique et de l'administration économique Paris)

## Sequential Analysis and Applications (Organizer: Alexander Tartakovsky)

### Asymptotically optimal control of FDR and related metrics for sequential multiple testing

Jay Bartroff (University of Southern California)

### Nearly optimal sequential detection of signals in correlated Gaussian noise

Grigory Sokolov (Xavier University)

To this end we examine three procedures: (i) an adaptive version of the sequential probability ratio test (SPRT) built upon one-stage delayed estimators of the unknown signal intensity; (ii) the generalized SPRT; and (iii) the non-adaptive double SPRT (2-SPRT). The generalized SPRT has certain drawbacks in selecting thresholds to guarantee the upper bounds on error probabilities, but may appear to be slightly more efficient than the adaptive SPRT.

However, simulations show that the loss in performance of the adaptive SPRT compared to the generalized SPRT is very minor, so—coupled with the error probability guarantee—the adaptive SPRT can be recommended for practical applications.

And although the non-adaptive 2-SPRT is not asymptotically optimal for all signal strength values, it does offer benefits at the worst point in the indifference zone.

Acknowledgement: The work of Alexander Tartakovsky was supported in part by the Russian Science Foundation Grant 18-19-00452 at the Moscow Institute of Physics and Technology.

### A unified approach for solving sequential selection problems

Yaakov Malinovsky (University of Maryland)

### Sequential change detection by optimal weighted l2 divergence

Yao Xie (Georgia Institute of Technology)

### Detection of temporary disorders

Michael Baron (American University)

### Q&A for Organized Contributed Session 29

###### Session Chair

Alexander Tartakovsky (Moscow Institute of Physics and Technology )