23 citations · 95 across the 16 of their papers we have counts for
17 papers
High-Dimensional Dynamic Pricing under Non-Stationarity: Learning and Earning with Change-Point Detection
Zifeng Zhao, Feiyu Jiang, Yi Yu +1
We consider a high-dimensional dynamic pricing problem under non-stationarity, where a firm sells products to sequentially arriving consumers that behave according to an unknow…
Probing Deep Speaker Embeddings for Speaker-related Tasks
Zifeng Zhao, Ding Pan, Junyi Peng +1
Deep speaker embeddings have shown promising results in speaker recognition, as well as in other speaker-related tasks. However, some issues are still under explored, for instance,…
Change point inference in high-dimensional regression models under temporal dependence
Haotian Xu, Daren Wang, Zifeng Zhao +1
This paper concerns about the limiting distributions of change point estimators, in a high-dimensional linear regression time series context, where a regression object $(y_t, X_t)…
Change-point Detection for Sparse and Dense Functional Data in General Dimensions
Carlos Misael Madrid Padilla, Daren Wang, Zifeng Zhao +1
We study the problem of change-point detection and localisation for functional data sequentially observed on a general d-dimensional space, where we allow the functional curves to…
Optimal Change-point Testing for High-dimensional Linear Models with Temporal Dependence
Zifeng Zhao, Xiaokai Luo, Zongge Liu +1
In this paper, we study change-point testing for high-dimensional linear models, an important problem that has not been well explored in the literature. Specifically, we propose a…
Speaker-Aware Mixture of Mixtures Training for Weakly Supervised Speaker Extraction
Zifeng Zhao, Rongzhi Gu, Dongchao Yang +2
Dominant researches adopt supervised training for speaker extraction, while the scarcity of ideally clean corpus and channel mismatch problem are rarely considered. To this end, we…
Target Confusion in End-to-end Speaker Extraction: Analysis and Approaches
Zifeng Zhao, Dongchao Yang, Rongzhi Gu +2
Recently, end-to-end speaker extraction has attracted increasing attention and shown promising results. However, its performance is often inferior to that of a blind source separat…
Functional Linear Regression with Mixed Predictors
Daren Wang, Zifeng Zhao, Yi Yu +1
We study a functional linear regression model that deals with functional responses and allows for both functional covariates and high-dimensional vector covariates. The proposed mo…
Functional Autoregressive Processes in Reproducing Kernel Hilbert Spaces
Daren Wang, Zifeng Zhao, Rebecca Willett +1
We study the estimation and prediction of functional autoregressive~(FAR) processes, a statistical tool for modeling functional time series data. Due to the infinite-dimensional na…
Time Series Analysis of COVID-19 Infection Curve: A Change-Point Perspective
Feiyu Jiang, Zifeng Zhao, Xiaofeng Shao
In this paper, we model the trajectory of the cumulative confirmed cases and deaths of COVID-19 (in log scale) via a piecewise linear trend model. The model naturally captures the…
Regression for Copula-linked Compound Distributions with Applications in Modeling Aggregate Insurance Claims
Peng Shi, Zifeng Zhao
In actuarial research, a task of particular interest and importance is to predict the loss cost for individual risks so that informative decisions are made in various insurance ope…
Change-point detection in dynamic networks via graphon estimation
Zifeng Zhao, Li Chen, Lizhen Lin
We propose a general approach for change-point detection in dynamic networks. The proposed method is model-free and covers a wide range of dynamic networks. The key idea behind our…
Alternating Pruned Dynamic Programming for Multiple Epidemic Change-Point Estimation
Zifeng Zhao, Chun Yip Yau
In this paper, we study the problem of multiple change-point detection for a univariate sequence under the epidemic setting, where the behavior of the sequence alternates between a…
Statistically and Computationally Efficient Change Point Localization in Regression Settings
Daren Wang, Zifeng Zhao, Kevin Lin +1
Detecting when the underlying distribution changes for the observed time series is a fundamental problem arising in a broad spectrum of applications. In this paper, we study multip…
A Composite Likelihood-based Approach for Change-point Detection in Spatio-temporal Processes
Zifeng Zhao, Ting Fung Ma, Wai Leong Ng +1
This paper develops a unified and computationally efficient method for change-point estimation along the time dimension in a non-stationary spatio-temporal process. By modeling a n…
Enhanced Pricing and Management of Bundled Insurance Risks with Dependence-aware Prediction using Pair Copula Construction
Peng Shi, Zifeng Zhao
We propose a dependence-aware predictive modeling framework for multivariate risks stemmed from an insurance contract with bundling features - an important type of policy increasin…
Modeling Multivariate Time Series with Copula-linked Univariate D-vines
Zifeng Zhao, Peng Shi, Zhengjun Zhang
This paper proposes a novel multivariate time series model named Copula-linked univariate D-vines (CuDvine), which enables the simultaneous copula-based modeling of both temporal a…