11 citations · 38 across the 12 of their papers we have counts for
12 papers
On tail-robust autocovariance matrix estimation for high-dimensional and potentially nonstationary time series
Haotian Xu, Stephane Guerrier, Runze Li +1
In this paper, we study the autocovariance matrix estimation and inference problems under heavy-tailedness, high-dimensionality, general nonlinear temporal dependence, and potentia…
Towards Open Science: Monitoring Crustal Deformations in North America
Lionel Voirol, Haotian Xu, Yuming Zhang +3
The study of the Earth's behavior has greatly benefited from the widespread deployment of Global Navigation Satellite Systems (GNSS), enabling large-scale monitoring of crustal def…
Change point detection and inference in multivariable nonparametric models under mixing conditions
Carlos Misael Madrid Padilla, Haotian Xu, Daren Wang +2
This paper studies multivariate nonparametric change point localization and inference problems. The data consists of a multivariate time series with potentially short range depende…
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)…
Online network change point detection with missing values and temporal dependence
Haotian Xu, Paromita Dubey, Yi Yu
In this paper we study online change point detection in dynamic networks with time heterogeneous missing pattern within networks and dependence across the time course. The missingn…
Localising change points in piecewise polynomials of general degrees
Yi Yu, Sabyasachi Chatterjee, Haotian Xu
In this paper we are concerned with a sequence of univariate random variables with piecewise polynomial means and independent sub-Gaussian noise. The underlying polynomials are all…
Robust Two-Step Wavelet-Based Inference for Time Series Models
Stéphane Guerrier, Roberto Molinari, Maria-Pia Victoria-Feser +1
Complex time series models such as (the sum of) ARMA models with additional noise, random walks, rounding errors and/or drifts are increasingly used for data analysis in fie…
Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration
Stéphane Guerrier, Juan Jurado, Mehran Khaghani +9
The task of inertial sensor calibration has required the development of various techniques to take into account the sources of measurement error coming from such devices. The calib…
Multivariate Signal Modelling with Applications to Inertial Sensor Calibration
Haotian Xu, Stéphane Guerrier, Roberto Molinari +1
The common approach to inertial sensor calibration for navigation purposes has been to model the stochastic error signals of individual sensors independently, whether as components…
A Study of the Allan Variance for Constant-Mean Non-Stationary Processes
Haotian Xu, Stéphane Guerrier, Roberto Molinari +1
The Allan Variance (AV) is a widely used quantity in areas focusing on error measurement as well as in the general analysis of variance for autocorrelated processes in domains such…
Joint Bayesian Gaussian discriminant analysis for speaker verification
Yiyan Wang, Haotian Xu, Zhijian Ou
State-of-the-art i-vector based speaker verification relies on variants of Probabilistic Linear Discriminant Analysis (PLDA) for discriminant analysis. We are mainly motivated by t…
Joint Stochastic Approximation learning of Helmholtz Machines
Haotian Xu, Zhijian Ou
Though with progress, model learning and performing posterior inference still remains a common challenge for using deep generative models, especially for handling discrete hidden v…