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The Kronecker coefficients are the decomposition multiplicities of the tensor product of two irreducible representations of the symmetric group. Unlike the Littlewood--Richardson coefficients, which are the analogues for the general linear…

Representation Theory · Mathematics 2023-06-09 Kyu-Hwan Lee

Multiway data analysis aims to uncover patterns in data structured as multi-indexed arrays, with multiway covariance playing a crucial role in many applications. However, the high dimensionality of multiway covariance presents significant…

Statistics Theory · Mathematics 2026-03-19 Dogyoon Song , Alfred O. Hero

We introduce a new approach for generating combinatorial identities and formulas by the application of Kronecker substitution to polynomial expansions within quotient rings. Our main result enables the derivation of elementary arithmetic…

General Mathematics · Mathematics 2024-11-26 Joseph M. Shunia

We propose a new approach to study the Kronecker coefficients by using the Schur-Weyl duality between the symmetric group and the partition algebra. We explain the limiting behavior and associated bounds in the context of the partition…

Representation Theory · Mathematics 2013-02-26 Christopher Bowman , Maud De Visscher , Rosa Orellana

Given a random quantum state of multiple distinguishable or indistinguishable particles, we provide an effective method, rooted in symplectic geometry, to compute the joint probability distribution of the eigenvalues of its one-body reduced…

Quantum Physics · Physics 2014-10-21 Matthias Christandl , Brent Doran , Stavros Kousidis , Michael Walter

The method of partial derivatives is one of the most successful lower bound methods for arithmetic circuits. It uses as a complexity measure the dimension of the span of the partial derivatives of a polynomial. In this paper, we consider…

Computational Complexity · Computer Science 2017-06-01 Ignacio Garcia-Marco , Pascal Koiran , Timothée Pecatte , Stéphan Thomassé

A critical milestone on the path to useful quantum computers is quantum supremacy - a demonstration of a quantum computation that is prohibitively hard for classical computers. A leading near-term candidate, put forth by the Google/UCSB…

Quantum Physics · Physics 2020-11-13 Adam Bouland , Bill Fefferman , Chinmay Nirkhe , Umesh Vazirani

We study the complexity of counting (weighted) planar graph homomorphism problem $\tt{Pl\text{-}GH}(M)$ parametrized by an arbitrary symmetric non-negative real valued matrix $M$. For matrices with pairwise distinct diagonal values, we…

Computational Complexity · Computer Science 2026-02-02 Jin-Yi Cai , Ashwin Maran , Ben Young

We study the query complexity of geodesically convex (g-convex) optimization on a manifold. To isolate the effect of that manifold's curvature, we primarily focus on hyperbolic spaces. In a variety of settings (smooth or not; strongly…

Optimization and Control · Mathematics 2023-07-25 Christopher Criscitiello , Nicolas Boumal

We discuss the geometry of orbit closures and the asymptotic behavior of Kronecker coefficients in the context of the Geometric Complexity Theory program to prove a variant of Valiant's algebraic analog of the P not equal to NP conjecture.…

Computational Complexity · Computer Science 2011-01-10 Peter Buergisser , J. M. Landsberg , Laurent Manivel , Jerzy Weyman

Tropical refined invariants of toric surfaces constitute a fascinating interpolation between real and complex enumerative geometries via tropical geometry. They were originally introduced by Block and G\"ottsche, and further extended by…

Combinatorics · Mathematics 2022-03-21 Erwan Brugallé , Andrés Jaramillo Puentes

In many high-dimensional problems, like sparse-PCA, planted clique, or clustering, the best known algorithms with polynomial time complexity fail to reach the statistical performance provably achievable by algorithms free of computational…

Statistics Theory · Mathematics 2025-06-17 Bertrand Even , Christophe Giraud , Nicolas Verzelen

Holant problems are a general framework to study the computational complexity of counting problems. It is a more expressive framework than counting constraint satisfaction problems (CSP) which are in turn more expressive than counting graph…

Computational Complexity · Computer Science 2025-04-22 Jin-Yi Cai , Jin Soo Ihm

In the past few years powerful generalizations to the Euclidean k-means problem have been made, such as Bregman clustering [7], co-clustering (i.e., simultaneous clustering of rows and columns of an input matrix) [9,18], and tensor…

Data Structures and Algorithms · Computer Science 2009-11-09 Stefanie Jegelka , Suvrit Sra , Arindam Banerjee

This paper describes an algorithm which computes the characteristic polynomial of a matrix over a field within the same asymptotic complexity, up to constant factors, as the multiplication of two square matrices. Previously, this was only…

Symbolic Computation · Computer Science 2021-04-12 Vincent Neiger , Clément Pernet

We consider the complexity of counting weighted graph homomorphisms defined by a symmetric matrix $A$. Each symmetric matrix $A$ defines a graph homomorphism function $Z_A(\cdot)$, also known as the partition function. Dyer and Greenhill…

Computational Complexity · Computer Science 2020-02-07 Artem Govorov , Jin-Yi Cai , Martin Dyer

The Kronecker coefficient g_{\lambda \mu \nu} is the multiplicity of the GL(V)\times GL(W)-irreducible V_\lambda \otimes W_\mu in the restriction of the GL(X)-irreducible X_\nu via the natural map GL(V)\times GL(W) \to GL(V \otimes W),…

Computational Complexity · Computer Science 2013-06-10 Jonah Blasiak , Ketan D. Mulmuley , Milind Sohoni

We construct an explicit field-independent SL$_2$-equivariant isomorphism between an invariant space of tensors and a plethysm space. The existence of such an isomorphism was only known in characteristic 0, and only indirectly via character…

Representation Theory · Mathematics 2026-05-05 Christian Ikenmeyer , Heidi Omar , Dimitrios Tsintsilidas

Positive definite kernels and their associated Reproducing Kernel Hilbert Spaces provide a mathematically compelling and practically competitive framework for learning from data. In this paper we take the approximation theory point of view…

Machine Learning · Computer Science 2018-08-06 Mikhail Belkin

These notes are an expanded version of a talk given by the second author. Our main interest is focused on the challenging problem of computing Kronecker coefficients. We decided, at the beginning, to take a very general approach to the…

Representation Theory · Mathematics 2015-06-09 Velleda Baldoni , Michele Vergne
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