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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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05/28/2023
Heterogeneous Matrix Factorization: When Features Differ by Datasets
In myriad statistical applications, data are collected from related but ...
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05/24/2023
Personalized Dictionary Learning for Heterogeneous Datasets
We introduce a relevant yet challenging problem named Personalized Dicti...
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07/17/2022
Personalized PCA: Decoupling Shared and Unique Features
In this paper, we tackle a significant challenge in PCA: heterogeneity. ...
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06/15/2022
Federated Data Analytics: A Study on Linear Models
As edge devices become increasingly powerful, data analytics are gradual...
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03/16/2022
A Continual Learning Framework for Adaptive Defect Classification and Inspection
Machine-vision-based defect classification techniques have been widely a...
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11/28/2021
Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling
In this paper, we propose : a Federated Gaussian process (𝒢𝒫) regression...
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11/19/2021
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits
Stochastic gradient descent (SGD) and its variants have established them...
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07/21/2021
Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning
In this paper we propose Fed-ensemble: a simple approach that bringsmode...
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02/19/2020
Weakly-supervised Multi-output Regression via Correlated Gaussian Processes
Multi-output regression seeks to infer multiple latent functions using d...
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11/04/2019
