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01/10/2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
Principal component analysis (PCA) is a classical and ubiquitous method ...
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12/05/2020
Selecting the number of components in PCA via random signflips
Dimensionality reduction via PCA and factor analysis is an important too...
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04/24/2020
Baseline Estimation of Commercial Building HVAC Fan Power Using Tensor Completion
Commercial building heating, ventilation, and air conditioning (HVAC) sy...
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06/04/2019
Stochastic Gradients for Large-Scale Tensor Decomposition
Tensor decomposition is a well-known tool for multiway data analysis. Th...
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02/21/2019
Convolutional Analysis Operator Learning: Dependence on Training Data
Convolutional analysis operator learning (CAOL) enables the unsupervised...
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10/30/2018
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
Modern applications increasingly involve high-dimensional and heterogene...
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08/22/2018
Generalized Canonical Polyadic Tensor Decomposition
Tensor decomposition is a fundamental unsupervised machine learning meth...
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11/17/2017
Instant Accident Reporting and Crowdsensed Road Condition Analytics for Smart Cities
The following report contains information about a proposed technology by...
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09/14/2017
Subspace Clustering using Ensembles of K-Subspaces
We present a novel approach to the subspace clustering problem that leve...
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10/12/2016
