50 citations · 72 across the 12 of their papers we have counts for
12 papers
Change-Point Detection for Object-valued Time Series
Yi Zhang, Changbo Zhu, Xiaofeng Shao
This article is concerned with change point detection for object-valued data that reside in a metric space, which has attracted some recent interests in statistics and econometrics…
Geodesic Optimal Transport Regression
Changbo Zhu, Hans-Georg Müller
Classical regression models do not cover non-Euclidean data that reside in a general metric space, while the current literature on non-Euclidean regression by and large has focused…
Two-Sample and Change-Point Inference for Non-Euclidean Valued Time Series
Feiyu Jiang, Changbo Zhu, Xiaofeng Shao
Data objects taking value in a general metric space have become increasingly common in modern data analysis. In this paper, we study two important statistical inference problems, n…
Testing Homogeneity: The Trouble with Sparse Functional Data
Changbo Zhu, Jane-Ling Wang
Testing the homogeneity between two samples of functional data is an important task. While this is feasible for intensely measured functional data, we explain why it is challenging…
Spherical Autoregressive Models, With Application to Distributional and Compositional Time Series
Changbo Zhu, Hans-Georg Müller
We introduce a new class of autoregressive models for spherical time series, where the dimension of the spheres on which the observations of the time series are situated may be fin…
Autoregressive Optimal Transport Models
Changbo Zhu, Hans-Georg Müller
Series of univariate distributions indexed by equally spaced time points are ubiquitous in applications and their analysis constitutes one of the challenges of the emerging field o…
Inference for Change Points in High Dimensional Data via Self-Normalization
Runmin Wang, Changbo Zhu, Stanislav Volgushev +1
This article considers change point testing and estimation for a sequence of high-dimensional data. In the case of testing for a mean shift for high-dimensional independent data, w…
Distance-based and RKHS-based Dependence Metrics in High Dimension
Changbo Zhu, Shun Yao, Xianyang Zhang +1
In this paper, we study distance covariance, Hilbert-Schmidt covariance (aka Hilbert-Schmidt independence criterion [Gretton et al. (2008)]) and related independence tests under th…
Interpoint Distance Based Two Sample Tests in High Dimension
Changbo Zhu, Xiaofeng Shao
In this paper, we study a class of two sample test statistics based on inter-point distances in the high dimensional and low sample size setting. Our test statistics include the we…
Online Gradient Descent in Function Space
Changbo Zhu, Huan Xu
In many problems in machine learning and operations research, we need to optimize a function whose input is a random variable or a probability density function, i.e. to solve optim…
Online Crowdsourcing
Changbo Zhu, Huan Xu, Shuicheng Yan
With the success of modern internet based platform, such as Amazon Mechanical Turk, it is now normal to collect a large number of hand labeled samples from non-experts. The Dawid-…
Generalized Singular Value Thresholding
Canyi Lu, Changbo Zhu, Chunyan Xu +2
This work studies the Generalized Singular Value Thresholding (GSVT) operator , \begin{equation*} {\text{Prox}}_{g}^{σ}(B)=\arg\min\limits_{X}\sum_{i=…