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In many applications such as data compression, imaging or genomic data analysis, it is important to approximate a given tensor by a tensor that is sparsely representable. For matrices, i.e. 2-tensors, such a representation can be obtained…

Numerical Analysis · Mathematics 2014-12-12 Shmuel Friedland , Venu Tammali

In many applications such as data compression, imaging or genomic data analysis, it is important to approximate a given tensor by a tensor that is sparsely representable. For matrices, i.e. 2-tensors, such a representation can be obtained…

Numerical Analysis · Mathematics 2008-05-29 S. Friedland , V. Mehrmann

This work considers a computationally and statistically efficient parameter estimation method for a wide class of latent variable models---including Gaussian mixture models, hidden Markov models, and latent Dirichlet allocation---which…

Machine Learning · Computer Science 2014-11-17 Anima Anandkumar , Rong Ge , Daniel Hsu , Sham M. Kakade , Matus Telgarsky

We study linear polynomial approximation of functions in weighted Sobolev spaces $W^r_{p,w}(\mathbb{R}^d)$ of mixed smoothness $r \in \mathbb{N}$, and their optimality in terms of Kolmogorov and linear $n$-widths of the unit ball…

Numerical Analysis · Mathematics 2025-01-03 Dinh Dũng

It is a classical result in rational approximation theory that certain non-smooth or singular functions, such as $|x|$ and $x^{1/p}$, can be efficiently approximated using rational functions with root-exponential convergence in terms of…

Numerical Analysis · Mathematics 2025-06-27 Kingsley Yeon , Steven B. Damelin

We established exact in order estimates an approximation of the Sobolev classes $W^{\boldsymbol{r}}_{p,\boldsymbol{\alpha}}(\mathbb{T}^d)$ of periodic functions of many variables with a bounded dominating mixed derivative. The approximation…

Classical Analysis and ODEs · Mathematics 2024-10-17 K. V. Pozharska , A. S. Romanyuk , S. Ya. Yanchenko

We study approximation properties of sequences of centered random elements $X_d$, $d\in\mathbb{N}$, with values in separable Hilbert spaces. We focus on sequences of tensor product-type random elements, which have covariance operators of…

Probability · Mathematics 2015-03-10 A. A. Khartov

We generalize the embedding formalism for conformal field theories to the case of general operators with mixed symmetry. The index-free notation encoding symmetric tensors as polynomials in an auxiliary polarization vector is extended to…

High Energy Physics - Theory · Physics 2015-09-03 Miguel S. Costa , Tobias Hansen

S. Ekhad and D. Zeilberger recently proved that the multivariate generating function for the number of simple singular vector tuples of a generic $m_1 \times \cdots \times m_d$ tensor has an elegant rational form involving elementary…

Combinatorics · Mathematics 2017-10-16 Jay Pantone

We provide a computational framework for approximating a class of structured matrices; here, the term structure is very general, and may refer to a regular sparsity pattern (e.g., block-banded), or be more highly structured (e.g., symmetric…

Numerical Analysis · Mathematics 2021-05-05 Misha E. Kilmer , Arvind K. Saibaba

The explicit expressions of the representation functions (D-functions) for Jordanian quantum group SL_h(2) are obtained by combination of tensor operator technique and Drinfeld twist. It is shown that the D-functions can be expressed in…

Quantum Algebra · Mathematics 2009-10-31 N. Aizawa

Bottom-Up Hidden Tree Markov Model is a highly expressive model for tree-structured data. Unfortunately, it cannot be used in practice due to the intractable size of its state-transition matrix. We propose a new approximation which lies on…

Machine Learning · Computer Science 2019-06-03 Daniele Castellana , Davide Bacciu

The statistical behaviour of a product of independent, identically distributed random matrices in $\text{SL}(2,{\mathbb R})$ is encoded in the generalised Lyapunov exponent $\Lambda$; this is a function whose value at the complex number $2…

Mathematical Physics · Physics 2019-11-04 Alain Comtet , Christophe Texier , Yves Tourigny

In this paper we introduce a new family of Bernstein-type exponential polynomials on the hypercube $[0, 1]^d$ and study their approximation properties. Such operators fix a multidimensional version of the exponential function and its…

Classical Analysis and ODEs · Mathematics 2024-05-28 Laura Angeloni , Danilo Costarelli , Chiara Darielli

A well known result from functional analysis states that any compact operator between Hilbert spaces admits a singular value decomposition (SVD). This decomposition is a powerful tool that is the workhorse of many methods both in…

Functional Analysis · Mathematics 2022-03-25 Mazen Ali , Anthony Nouy

Emphasis in the tensor literature on random embeddings (tools for low-distortion dimension reduction) for the canonical polyadic (CP) tensor decomposition has left analogous results for the more expressive Tucker decomposition comparatively…

Machine Learning · Statistics 2024-06-14 Matthew Pietrosanu , Bei Jiang , Linglong Kong

We study low rank approximation of tensors, focusing on the tensor train and Tucker decompositions, as well as approximations with tree tensor networks and more general tensor networks. For tensor train decomposition, we give a bicriteria…

Data Structures and Algorithms · Computer Science 2023-11-28 Arvind V. Mahankali , David P. Woodruff , Ziyu Zhang

We consider arbitrary algebraic families of lower order deformations of nondegenerate toric exponential sums over a finite field. We construct a relative polytope with the aid of which we define a ring of coefficients consisting of p-adic…

Number Theory · Mathematics 2013-07-02 C. Douglas Haessig , Steven Sperber

We introduce and extend the outer product and contractive product of tensors and matrices, and present some identities in terms of these products. We offer tensor expressions of derivatives of tensors, focus on the tensor forms of…

Classical Analysis and ODEs · Mathematics 2025-09-22 Yiran Xu , Guangbin Wang , Changqing Xu

In this paper we study the asymptotic behavior of the number of summands in tensor products of finite dimensional representations of affine (semi)group (super)schemes and related objects.

Representation Theory · Mathematics 2024-12-11 Kevin Coulembier , Victor Ostrik , Daniel Tubbenhauer