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Found 3 papers, 1 papers with code
Exact Clustering in Tensor Block Model: Statistical Optimality and Computational Limit
High-order clustering aims to identify heterogeneous substructures in multiway datasets that arise commonly in neuroimaging, genomics, social network studies, etc.
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation
Under mild conditions on the loss function, we establish both an upper bound on statistical error and the linear rate of computational convergence through a general deterministic analysis.
Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data
In this article, we consider the sparse tensor singular value decomposition, which aims for dimension reduction on high-dimensional high-order data with certain sparsity structure.
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