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09/07/2023
Personalized Tucker Decomposition: Modeling Commonality and Peculiarity on Tensor Data
We propose personalized Tucker decomposition (perTucker) to address the ...
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07/04/2023
Minimax rates for latent position estimation in the generalized random dot product graph
Latent space models play an important role in the modeling and analysis ...
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06/23/2023
Tensor Dirichlet Process Multinomial Mixture Model for Passenger Trajectory Clustering
Passenger clustering based on travel records is essential for transporta...
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05/24/2023
Interpretation and visualization of distance covariance through additive decomposition of correlations formula
Distance covariance is a widely used statistical methodology for testing...
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05/14/2023
Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing
Interactive semantic parsing based on natural language (NL) feedback, wh...
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12/15/2022
Dual Moving Average Pseudo-Labeling for Source-Free Inductive Domain Adaptation
Unsupervised domain adaptation reduces the reliance on data annotation i...
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10/26/2022
Learning on Large-scale Text-attributed Graphs via Variational Inference
This paper studies learning on text-attributed graphs (TAGs), where each...
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10/16/2022
Posterior Regularized Bayesian Neural Network Incorporating Soft and Hard Knowledge Constraints
Neural Networks (NNs) have been widely used in supervised learning due t...
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08/09/2022
Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detection
In this paper, we present an efficient statistical method (denoted as "A...
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08/09/2022
Adaptive Partially-Observed Sequential Change Detection and Isolation
High-dimensional data has become popular due to the easy accessibility o...
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05/07/2022
Multi-View Video Coding with GAN Latent Learning
The introduction of multiple viewpoints inevitably increases the bitrate...
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02/25/2022
ANTLER: Bayesian Nonlinear Tensor Learning and Modeler for Unstructured, Varying-Size Point Cloud Data
Unstructured point clouds with varying sizes are increasingly acquired i...
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09/20/2021
Deep Spatio-temporal Sparse Decomposition for Trend Prediction and Anomaly Detection in Cardiac Electrical Conduction
Electrical conduction among cardiac tissue is commonly modeled with part...
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05/17/2021
Deep Multistage Multi-Task Learning for Quality Prediction of Multistage Manufacturing Systems
In multistage manufacturing systems, modeling multiple quality indices b...
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01/18/2021
Adaptive Change Point Monitoring for High-Dimensional Data
In this paper, we propose a class of monitoring statistics for a mean sh...
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09/22/2020
Partially Observable Online Change Detection via Smooth-Sparse Decomposition
We consider online change detection of high dimensional data streams wit...
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08/15/2020
Automatic Storage Structure Selection for hybrid Workload
In the use of database systems, the design of the storage engine and dat...
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04/23/2020
Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile
Spatiotemporal data is very common in many applications, such as manufac...
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04/23/2020
Real-time Detection of Clustered Events in Video-imaging data with Applications to Additive Manufacturing
The use of video-imaging data for in-line process monitoring application...
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04/23/2020
Rapid Detection of Hot-spots via Tensor Decomposition with applications to Crime Rate Data
We propose an efficient statistical method (denoted as SSR-Tensor) to ro...
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01/31/2020
Rapid Detection of Hot-spot by Tensor Decomposition with Application to Weekly Gonorrhea Data
In many bio-surveillance and healthcare applications, data sources are m...
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12/11/2019
Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction
Low-rank tensor decomposition and completion have attracted significant ...
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11/01/2019
High-dimensional Nonlinear Profile Monitoring based on Deep Probabilistic Autoencoders
Wide accessibility of imaging and profile sensors in modern industrial s...
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10/04/2019
AKM^2D : An Adaptive Framework for Online Sensing and Anomaly Quantification
In point-based sensing systems such as coordinate measuring machines (CM...
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06/09/2019
Dynamic Network Embedding via Incremental Skip-gram with Negative Sampling
Network representation learning, as an approach to learn low dimensional...
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07/26/2018
Structured Point Cloud Data Analysis via Regularized Tensor Regression for Process Modeling and Optimization
Advanced 3D metrology technologies such as Coordinate Measuring Machine ...
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04/11/2018
Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning
Multivariate functional data from a complex system are naturally high-di...
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02/28/2018
A novel approach for fusion of heterogeneous sources of data
With advancements in sensor technology, a heterogeneous set of data, con...
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02/28/2018