4 citations · 23 across the 17 of their papers we have counts for
17 papers
An Efficient Continual Learning Framework for Multivariate Time Series Prediction Tasks with Application to Vehicle State Estimation
Arvin Hosseinzadeh, Ladan Khoshnevisan, Mohammad Pirani +2
In continual time series analysis using neural networks, catastrophic forgetting (CF) of previously learned models when training on new data domains has always been a significant c…
Graph-based Change Point Detection for Functional Data
Jeremy VanderDoes, Shojaeddin Chenouri
Modeling functions that are sequentially observed as functional time series is becoming increasingly common. In such models, it is often crucial to ensure data homogeneity. We inve…
A Comprehensive Framework for Statistical Inference in Measurement System Assessment Studies
Banafsheh Lashkari, Shojaeddin Chenouri
Measurement system analysis aims to quantify the variability in data attributable to the measurement system and evaluate its contribution to overall data variability. This paper co…
Differentially private multivariate medians
Kelly Ramsay, Aukosh Jagannath, Shoja'eddin Chenouri
Statistical tools which satisfy rigorous privacy guarantees are necessary for modern data analysis. It is well-known that robustness against contamination is linked to differential…
Robust changepoint detection in the variability of multivariate functional data
Kelly Ramsay, Shoja'eddin Chenouri
We consider the problem of robustly detecting changepoints in the variability of a sequence of independent multivariate functions. We develop a novel changepoint procedure, called…
Functional Boxplots for Outlier Detection in Additive Manufacturing
Ahmad Mozaffari, Shojaeddin Chenouri, Ehsan Toyserkani +1
Additive manufacturing (AM), also known as 3D printing, is one of the most promising digital manufacturing technologies, thanks to its potential to produce highly complex geometrie…
On Monitoring High-Dimensional Processes with Individual Observations
Mohsen Ebadi, Shojaeddin Chenouri, Stefan H. Steiner
Modern data collecting methods and computation tools have made it possible to monitor high-dimensional processes. In this article, Phase II monitoring of high-dimensional processes…
Phase I Analysis of High-Dimensional Processes in the Presence of Outliers
Mohsen Ebadi, Shojaeddin Chenouri, Stefan H. Steiner
One of the significant challenges in monitoring the quality of products today is the high dimensionality of quality characteristics. In this paper, we address Phase I analysis of h…
Robust nonparametric hypothesis tests for differences in the covariance structure of functional data
Kelly Ramsay, Shojaeddin Chenouri
We develop a group of robust, nonparametric hypothesis tests which detect differences between the covariance operators of several populations of functional data. These tests, calle…
Valid Post-Detection Inference for Change Points Identified Using Trend Filtering
Reza Valiollahi Mehrizi, Shojaeddin Chenouri
There are many research works and methods about change point detection in the literature. However, there are only a few that provide inference for such change points after being es…
Differentially private depth functions and their associated medians
Kelly Ramsay, Shoja'eddin Chenouri
In this paper, we investigate the differentially private estimation of data depth functions and their associated medians. We introduce several methods for privatizing depth values…
A non-alternating graph hashing algorithm for large scale image search
Sobhan Hemati, Mohammad Hadi Mehdizavareh, Shojaeddin Chenouri +1
In the era of big data, methods for improving memory and computational efficiency have become crucial for successful deployment of technologies. Hashing is one of the most effectiv…
Robust multiple change-point detection for multivariate variability using data depth
Kelly Ramsay, Shoja'eddin Chenouri
In this paper, we introduce two robust, nonparametric methods for multiple change-point detection in the variability of a multivariate sequence of observations. We demonstrate that…
Detection of Change Points in Piecewise Polynomial Signals Using Trend Filtering
Reza V. Mehrizi, Shojaeddin Chenouri
While many approaches have been proposed for discovering abrupt changes in piecewise constant signals, few methods are available to capture these changes in piecewise polynomial si…
Statistical Monitoring of the Covariance Matrix in Multivariate Processes: A Literature Review
Mohsen Ebadi, Shoja'eddin Chenouri, Dennis K. J. Lin +1
Monitoring several correlated quality characteristics of a process is common in modern manufacturing and service industries. Although a lot of attention has been paid to monitoring…
A New Method for Performance Analysis in Nonlinear Dimensionality Reduction
Jiaxi Liang, Shojaeddin Chenouri, Christopher G. Small
In this paper, we develop a local rank correlation measure which quantifies the performance of dimension reduction methods. The local rank correlation is easily interpretable, and…
Optimal estimation in functional linear regression for sparse noise-contaminated data
Behdad Mostafaiy, MohammadReza FaridRohani, Shojaeddin Chenouri
In this paper, we propose a novel approach to fit a functional linear regression in which both the response and the predictor are functions of a common variable such as time. We co…