Articles with "tensor train" as a keyword



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Block tensor train decomposition for missing data estimation

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Published in 2018 at "Statistical Papers"

DOI: 10.1007/s00362-018-1043-8

Abstract: We propose a method for imputation of missing values in large scale matrix data based on a low-rank tensor approximation technique called the block tensor train (BTT) decomposition. Given sparsely observed data points, the proposed… read more here.

Keywords: tensor train; tensor; block tensor; method ... See more keywords
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Randomized algorithms for the approximations of Tucker and the tensor train decompositions

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Published in 2019 at "Advances in Computational Mathematics"

DOI: 10.1007/s10444-018-9622-8

Abstract: Randomized algorithms provide a powerful tool for scientific computing. Compared with standard deterministic algorithms, randomized algorithms are often faster and robust. The main purpose of this paper is to design adaptive randomized algorithms for computing… read more here.

Keywords: tensor train; adaptive randomized; tensor; algorithms approximations ... See more keywords
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A continuous analogue of the tensor-train decomposition

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Published in 2019 at "Computer Methods in Applied Mechanics and Engineering"

DOI: 10.1016/j.cma.2018.12.015

Abstract: We describe a new function approximation framework based on a continuous extension of the tensor-train decomposition. The approximation, termed a function-train (FT), results in a tensor-train structure whose cores are univariate functions. An advantage of… read more here.

Keywords: tensor train; approximation; train decomposition;
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Functional Tensor-Train Chebyshev Method for Multidimensional Quantum Dynamics Simulations.

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Published in 2021 at "Journal of chemical theory and computation"

DOI: 10.1021/acs.jctc.1c00941

Abstract: Methods for efficient simulations of multidimensional quantum dynamics are essential for theoretical studies of chemical systems where quantum effects are important, such as those involving rearrangements of protons or electronic configurations. Here, we introduce the… read more here.

Keywords: quantum; quantum dynamics; multidimensional quantum; tensor train ... See more keywords
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Tensor-Train Thermo-Field Memory Kernels for Generalized Quantum Master Equations.

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Published in 2022 at "Journal of chemical theory and computation"

DOI: 10.1021/acs.jctc.2c00892

Abstract: The generalized quantum master equation (GQME) approach provides a rigorous framework for deriving the exact equation of motion for any subset of electronic reduced density matrix elements (e.g., the diagonal elements). In the context of… read more here.

Keywords: tensor train; train thermo; memory; memory kernels ... See more keywords

Data Driven Prognosis of Fracture Dynamics Using Tensor Train and Gaussian Process Regression

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Published in 2020 at "IEEE Access"

DOI: 10.1109/access.2020.3042830

Abstract: Accurate prediction of the mechanical failure of structural components plays an important role in the design of engineering structures. However, the fracture process is challenging to model numerically due to the existence of an elastic… read more here.

Keywords: process; fracture; model; process regression ... See more keywords
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Application of Tensor Train Decomposition in S2VT Model for Sign Language Recognition

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Published in 2021 at "IEEE Access"

DOI: 10.1109/access.2021.3059660

Abstract: Sign language recognition is a conversion of sign language into text or speech, bridging the communication between the hearing and society. Recently, sequence-to-sequence video to text (S2VT) models has been employed in the field of… read more here.

Keywords: tensor train; s2vt; tensor; sign language ... See more keywords
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TT-MLP: Tensor Train Decomposition on Deep MLPs

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Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3240784

Abstract: Deep multilayer perceptrons (MLPs) have achieved promising performance on computer vision tasks. Deep MLPs consist solely of fully-connected layers as the conventional MLPs do but adopt more sophisticated network architectures based on mixer layers composed… read more here.

Keywords: tensor train; train decomposition; deep mlps; train ... See more keywords

Video Scene Segmentation Using Tensor-Train Faster-RCNN for Multimedia IoT Systems

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Published in 2021 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2020.3022353

Abstract: Video surveillance techniques like scene segmentation are playing an increasingly important role in multimedia Internet-of-Things (IoT) systems. However, existing deep learning-based methods face challenges in both accuracy and memory when deployed on edge computing devices… read more here.

Keywords: iot systems; scene segmentation; scene; segmentation ... See more keywords
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Fast and Accurate Tensor Completion With Total Variation Regularized Tensor Trains

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Published in 2020 at "IEEE Transactions on Image Processing"

DOI: 10.1109/tip.2020.2995061

Abstract: We propose a new tensor completion method based on tensor trains. The to-be-completed tensor is modeled as a low-rank tensor train, where we use the known tensor entries and their coordinates to update the tensor… read more here.

Keywords: tensor; completion; tensor completion; tensor train ... See more keywords
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Tensor-Train Decomposition in the Presence of Interval-Valued Data

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Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2021.3135715

Abstract: In many fields of computer science, tensor decomposition techniques are increasingly being adopted as the core of many applications that rely on multi-dimensional datasets for implementing knowledge discovery tasks. Unfortunately, a major shortcoming of state-of-the-art… read more here.

Keywords: tensor train; tensor; valued data; interval valued ... See more keywords