Sketch-based multiplicative updating algorithms for symmetric nonnegative tensor factorizations with applications to face image clustering
DOI10.1007/s10898-024-01374-4zbMATH Open1546.15011MaRDI QIDQ6593833
Mao-Lin Che, Hong Yan, Yimin Wei
Publication date: 27 August 2024
Published in: Journal of Global Optimization (Search for Journal in Brave)
sketchingrandom samplingrandom projectionsymmetric nonnegative tensor factorizationmultiplicative updating algorithms
Factorization of matrices (15A23) Matrix equations and identities (15A24) Eigenvalues, singular values, and eigenvectors (15A18) Multilinear algebra, tensor calculus (15A69) Randomized algorithms (68W20) Numerical methods for low-rank matrix approximation; matrix compression (65F55)
Cites Work
- Unnamed Item
- Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
- Tensor Decompositions and Applications
- Tensor-Train Decomposition
- \(\{0,1\}\) completely positive tensors and multi-hypergraphs
- A semidefinite algorithm for completely positive tensor decomposition
- Families of alpha-, beta- and gamma-divergences: flexible and robust measures of similarities
- Randomized interpolative decomposition of separated representations
- Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework
- Robust parameter estimation with a small bias against heavy contamination
- Randomized LU decomposition
- Fast randomized matrix and tensor interpolative decomposition using countsketch
- Faster tensor train decomposition for sparse data
- Multiplicative algorithms for symmetric nonnegative tensor factorizations and its applications
- Randomized algorithms for the low multilinear rank approximations of tensors
- Numerical optimization for symmetric tensor decomposition
- Eigenvalues of a real supersymmetric tensor
- Smallest singular value of random matrices and geometry of random polytopes
- Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
- Randomized algorithms for the approximations of Tucker and the tensor train decompositions
- Completely Positive Tensors: Properties, Easily Checkable Subclasses, and Tractable Relaxations
- A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion
- Uniqueness of Nonnegative Tensor Approximations
- IMPROVED ANALYSIS OF THE SUBSAMPLED RANDOMIZED HADAMARD TRANSFORM
- Newton-based optimization for Kullback–Leibler nonnegative tensor factorizations
- Smallest singular value of a random rectangular matrix
- Robust and efficient estimation by minimising a density power divergence
- Numerical Optimization
- A Multilinear Singular Value Decomposition
- Nesterov-Based Alternating Optimization for Nonnegative Tensor Factorization: Algorithm and Parallel Implementation
- A Practical Randomized CP Tensor Decomposition
- On Tensors, Sparsity, and Nonnegative Factorizations
- Randomized Algorithms for Low-Rank Tensor Decompositions in the Tucker Format
- Low-Rank Tucker Approximation of a Tensor from Streaming Data
- The Computation of Low Multilinear Rank Approximations of Tensors via Power Scheme and Random Projection
- Tensor Train Construction From Tensor Actions, With Application to Compression of Large High Order Derivative Tensors
- Theory and Computation of Complex Tensors and its Applications
- Nonnegative Tensor Factorization, Completely Positive Tensors, and a Hierarchical Elimination Algorithm
- Recompression of Hadamard Products of Tensors in Tucker Format
- Fast monte-carlo algorithms for finding low-rank approximations
- Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication
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