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Paper Citation Record · LEDGER

Kernel Regression with Tensor Trains and Hadamard Overparameterization

As of 8 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2607.17390.

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2607.17390 v2

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measured 71 of 71 reference resolution

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Outbound references

Observation bd988220-e57a-47be-b2e9-6e75f9fe8e50 · outbound

This paper cites Tensordecompositionforsignalprocessing andmachinelearning,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensordecompositionforsignalprocessing andmachinelearning,

Reference 1

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This paper cites Tensorcompletionalgorithmsinbigdataanalytics,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensorcompletionalgorithmsinbigdataanalytics,

Reference 2

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This paper cites Tensor-traindecomposition,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensor-traindecomposition,

Reference 3

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This paper cites Tensor Ring Decomposition.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensor Ring Decomposition

Reference 4

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This paper cites Tensor-train decomposition for image classification problems,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensor-train decomposition for image classification problems,

Reference 5

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This paper cites The Tucker and Tensor Train decompositions,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization The Tucker and Tensor Train decompositions,

Reference 6

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This paper cites On manifolds of tensors of fixed TT-rank,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization On manifolds of tensors of fixed TT-rank,

Reference 7

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This paper cites Berlin: Springer,2022.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Berlin: Springer,2022

Reference 8

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This paper cites Theoryofreproducingkernels,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Theoryofreproducingkernels,

Reference 9

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This paper cites Cambridge,MA:MITPress,2002.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Cambridge,MA:MITPress,2002

Reference 10

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This paper cites Some results on Tchebycheffian spline functions,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Some results on Tchebycheffian spline functions,

Reference 11

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This paper cites Nonparametric low-rank tensor imputation,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Nonparametric low-rank tensor imputation,

Reference 12

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This paper cites Tensor Decomposition Meets RKHS: Efficient Algorithms for Smooth and Misaligned Data.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensor Decomposition Meets RKHS: Efficient Algorithms for Smooth and Misaligned Data

Reference 13

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This paper cites When bayesian tensor completion meets multioutput gaussian processes: Functional universality and rank learning,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization When bayesian tensor completion meets multioutput gaussian processes: Functional universality and rank learning,

Reference 14

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This paper cites Kernel-based tensor partial least squares for reconstruction of limb move- ments,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Kernel-based tensor partial least squares for reconstruction of limb move- ments,

Reference 15

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Gradient-based optimization for regression in the functional tensor-train format,

Reference 16

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Kernel Bayesian tensor ring decomposition for multiway data recovery,

Reference 17

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This paper cites Györfi, M.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Györfi, M

Reference 18

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Multilinear kernel regression and imputation via manifold learning,

Reference 19

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Imputation of time-varying edge flows in graphs by multilinear kernel regression and manifoldlearning,

Reference 20

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Estimating dynamic graph flows with kernel models and Hadamard-structured Riemannian constraints,

Reference 21

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Riemannianoptimizationforhigh-dimensionaltensorcompletion,

Reference 22

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Taking the 4D nature of fMRI data into account promises significant gains in data completion,

Reference 23

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Kernel Regression with Tensor Trains and Hadamard Overparameterization LASSO, fractional norm and structured sparse estimation using a Hadamard product parametrization,

Reference 24

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This paper cites The tail-Hadamard product parametrization algorithm for compressed sensing,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization The tail-Hadamard product parametrization algorithm for compressed sensing,

Reference 25

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Kernel Regression with Tensor Trains and Hadamard Overparameterization SPRED:solving L1 penaltywithSGD,

Reference 26

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization

Reference 27

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Kernel regression via tensor trains with Hadamard overparametrization and imputationofdynamicgraphedgeflows,

Reference 28

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Kernel Regression with Tensor Trains and Hadamard Overparameterization LearninggeneralGaussiankernelhyperparametersofSVMsusingoptimization onsymmetricpositive-definitematricesmanifold,

Reference 29

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensordecompositionsandapplications,

Reference 30

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensor networks for dimensionality reduction and large- scale optimization—Part 1: Low-rank tensor decompositions,

Reference 31

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Kernel Regression with Tensor Trains and Hadamard Overparameterization PrincetonUniversityPress,2008

Reference 32

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Geometric methods on low-rank matrix and tensor manifolds,

Reference 33

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Nonlinear dimensionality reduction by locally linear embedding,

Reference 34

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Sparsemanifoldclusteringandembedding,

Reference 35

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Using the Nyström method to speed up kernel machines,

Reference 36

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Sparse multidimensional scaling using landmark points,

Reference 37

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Kernel Regression with Tensor Trains and Hadamard Overparameterization Unconstrainedparametrizationsforvariance-covariancematrices,

Reference 38

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Observation b72e2bc0-6d37-4b33-a196-23160f6bbdb2 · outbound

This paper cites Springer,2006.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Springer,2006

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Observation 1e1ddd2d-adad-4f69-bfbc-5033fe6ed655 · outbound

This paper cites Low-rank matrix completion by Riemannian optimization,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Low-rank matrix completion by Riemannian optimization,

Reference 40

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Observation a1c3e20f-0786-4150-9655-ec1beee9b634 · outbound

This paper cites Tensorringdecomposition: Optimizationlandscapeandone-loopconvergenceofalternatingleastsquares,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensorringdecomposition: Optimizationlandscapeandone-loopconvergenceofalternatingleastsquares,

Reference 41

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Observation 23265c35-73e8-48e6-9ea1-d5d7bbfe0d50 · outbound

This paper cites Riemannian preconditioned algorithms for tensor completion via tensor ring decomposition,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Riemannian preconditioned algorithms for tensor completion via tensor ring decomposition,

Reference 42

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Observation ce33fddd-3dc5-4132-8799-1c0736b2a4ae · outbound

This paper cites Impact oftheresolutionofbrainparcelsonconnectome-wideassociationstudiesinfMRI,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Impact oftheresolutionofbrainparcelsonconnectome-wideassociationstudiesinfMRI,

Reference 43

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Observation e3ca6b03-41a5-4bd4-bdcf-31b8163df3ff · outbound

This paper cites BOLD5000, a public fMRI dataset while viewing 5000 visualimages,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization BOLD5000, a public fMRI dataset while viewing 5000 visualimages,

Reference 44

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Observation 8db2f87b-a667-4dfa-8e80-232f13a3ad2e · outbound

This paper cites fMRIPrep: arobustpreprocessingpipelineforfunctionalMRI,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization fMRIPrep: arobustpreprocessingpipelineforfunctionalMRI,

Reference 45

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Observation 10994cd2-26f9-4b39-be72-93d7ea0dbdc3 · outbound

This paper cites Data adaptive RKHS Tikhonov regularization for learning kernels in operators,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Data adaptive RKHS Tikhonov regularization for learning kernels in operators,

Reference 46

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Observation 6fab9d5c-e1fb-468b-9356-a54d376ead6d · outbound

This paper cites CambridgeUniversityPress,2010.

Kernel Regression with Tensor Trains and Hadamard Overparameterization CambridgeUniversityPress,2010

Reference 47

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Observation 2059d98b-aebd-4127-95d5-0572ed05f1c9 · outbound

This paper cites HodgeLaplaciansongraphs,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization HodgeLaplaciansongraphs,

Reference 48

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Observation b91f4e81-dd9c-4733-9d41-5b1d10d017c8 · outbound

This paper cites Signal processing on higher-order networks: Livin’ on the edge...andbeyond,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Signal processing on higher-order networks: Livin’ on the edge...andbeyond,

Reference 49

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Observation 71b6c1e2-6bea-436a-848b-096c5599c86c · outbound

This paper cites Topological signal processing over simplicial complexes,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Topological signal processing over simplicial complexes,

Reference 50

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Observation 905d29c5-f3fc-43a3-a86c-56f5ffb27e27 · outbound

This paper cites Networksbeyondpairwiseinteractions: Structureanddynamics,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Networksbeyondpairwiseinteractions: Structureanddynamics,

Reference 51

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Observation 65c8b256-8b72-4341-bd06-a7953163bc97 · outbound

This paper cites Simplicial vector autoregressive models,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Simplicial vector autoregressive models,

Reference 52

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Observation 5e3d686e-3d87-4224-9c6b-522858fa50ff · outbound

This paper cites Evolutionbackcastingofedgeflowsfrompartialobservationsusingsimplicial vectorautoregressivemodels,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Evolutionbackcastingofedgeflowsfrompartialobservationsusingsimplicial vectorautoregressivemodels,

Reference 53

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Observation 581da534-a97b-4710-aba5-d01cc5c53583 · outbound

This paper cites Hodge-compositional edge Gaussian processes,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Hodge-compositional edge Gaussian processes,

Reference 54

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Observation e3962a23-8632-44b7-baa8-6a567a02f830 · outbound

This paper cites Simplicial neural networks,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Simplicial neural networks,

Reference 55

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Observation 62407065-c0c2-4ae8-978e-5e61a28862c8 · outbound

This paper cites Principledsimplicialneuralnetworksfortrajectoryprediction,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Principledsimplicialneuralnetworksfortrajectoryprediction,

Reference 56

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Observation 7dcbefae-0081-4bd6-8cd6-77462637a378 · outbound

This paper cites Simplicialconvolutionalneuralnetworks,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Simplicialconvolutionalneuralnetworks,

Reference 57

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Observation bd8a8c68-3fd7-4ed0-9de2-6c8e597a34e2 · outbound

This paper cites Simplicial complex neural networks,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Simplicial complex neural networks,

Reference 58

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Observation 7f615e06-111c-4586-873b-86effc835e2b · outbound

This paper cites Position: Topologicaldeeplearningisthenewfrontierforrelationallearning,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Position: Topologicaldeeplearningisthenewfrontierforrelationallearning,

Reference 59

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Observation a9ce7ba1-a3d0-4349-ba3f-36e4c72434e2 · outbound

This paper cites Transportation networks for research,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Transportation networks for research,

Reference 60

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Observation 138d53f8-00d7-4fc5-8887-ffcefafe13b7 · outbound

This paper cites UXsim: LightweightmesoscopictrafficflowsimulatorinpurePython,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization UXsim: LightweightmesoscopictrafficflowsimulatorinpurePython,

Reference 61

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Observation 062cfb2b-d4e5-420a-b2ae-f6701512a486 · outbound

This paper cites Signal processing on product spaces,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Signal processing on product spaces,

Reference 62

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Observation 9cc5cf7d-a557-4037-a5e0-4d2041f9fcfa · outbound

This paper cites HodgeNet: Graphneuralnetworksforedgedata,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization HodgeNet: Graphneuralnetworksforedgedata,

Reference 63

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Observation d190feed-d81e-4bcc-96d8-efcab12711d8 · outbound

This paper cites Robusttensorringdecompositionforurbantrafficdataimputation,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Robusttensorringdecompositionforurbantrafficdataimputation,

Reference 64

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Observation 7f6d8d62-2344-4f2d-bbf0-e8ad7cd473be · outbound

This paper cites Tensordenoisingusinglow-ranktensortraindecomposition,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Tensordenoisingusinglow-ranktensortraindecomposition,

Reference 65

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Observation 75b02a8e-532e-434f-9eb6-39e8330785a0 · outbound

This paper cites MosttensorproblemsareNP-hard,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization MosttensorproblemsareNP-hard,

Reference 66

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Observation 9f52fc58-7fe1-473b-bd97-55447f8b841d · outbound

This paper cites Projection-likeretractionsonmatrixmanifolds,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Projection-likeretractionsonmatrixmanifolds,

Reference 67

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Observation d98ca063-e4bf-4335-a979-8d2564d83a86 · outbound

This paper cites Time integration of tensor trains,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Time integration of tensor trains,

Reference 68

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Observation f4e52930-6da6-4334-83c5-8ad9fca288d9 · outbound

This paper cites quasi-optimal.

Kernel Regression with Tensor Trains and Hadamard Overparameterization quasi-optimal

Reference 69

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Observation 6da666bc-359b-421b-8483-ba072ab32c54 · outbound

This paper cites Cν isderivedbythechainruleofdifferentiationasfollows ∂L ∂X (i1,.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Cν isderivedbythechainruleofdifferentiationasfollows ∂L ∂X (i1,

Reference 70

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Observation 604a7e71-a59e-4b6d-829c-ea5cf99c5fd2 · outbound

This paper cites Therefore,theEuclideangradientw.r.t.

Kernel Regression with Tensor Trains and Hadamard Overparameterization Therefore,theEuclideangradientw.r.t

Reference 71

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Pith citing papers

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