5 papers
Kernel Regression with Tensor Trains and Hadamard Overparameterization
Duc Thien Nguyen, Konstantinos Slavakis, Eleftherios Kofidis +1
Kernel regression with tensor trains and Hadamard overparameterization (KReTTaH) is introduced as a training-data-free, interpretable, and nonparametric framework for multi-way dat…
Beyond Tensor Probabilistic Independent Component Analysis -- Putting Block-Term Decomposition and Independent Vector Analysis Together
Eleftherios Kofidis
Tensor probabilistic independent component analysis (TPICA) is a popular approach to analyzing functional magnetic resonance imaging (fMRI) data, which draws its popularity from it…
Block-Term Decomposition Approach to Blind Multi-trial Functional Ultrasound Unmixing
Sofia-Eirini Kotti, Eleftherios Kofidis, Borbála Hunyadi
Functional ultrasound (fUS) has emerged as a powerful neuroimaging modality due to its high resolution in both space and time, low cost and potential portability. Nevertheless, fUS…
Kernel Regression of Multi-Way Data via Tensor Trains with Hadamard Overparametrization: The Dynamic Graph Flow Case
Duc Thien Nguyen, Konstantinos Slavakis, Eleftherios Kofidis +1
A regression-based framework for interpretable multi-way data imputation, termed Kernel Regression via Tensor Trains with Hadamard overparametrization (KReTTaH), is introduced. KRe…
Federated Learning Using Coupled Tensor Train Decomposition
Xiangtao Zhang, Eleftherios Kofidis, Ce Zhu +2
Coupled tensor decomposition (CTD) can extract joint features from multimodal data in various applications. It can be employed for federated learning networks with data confidentia…