Results 11 to 20 of about 3,545,396 (319)
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Symmetric nonnegative matrix trifactorization
Linear Algebra and its Applications, 2023 The Symmetric Nonnegative Matrix Trifactorization (SN-Trifactorization) is a factorization of an $n \times n$ nonnegative symmetric matrix $A$ of the form $BCB^T$, where $C$ is a $k \times k$ symmetric matrix, and both $B$ and $C$ are required to be nonnegative.
Damjana Kokol Bukovšek, Helena Šmigoc
openaire +2 more sources
A Hebbian/Anti-Hebbian network for online sparse dictionary learning derived from symmetric matrix factorization [PDF]
Asilomar Conference on Signals, Systems and Computers, 2014 Olshausen and Field (OF) proposed that neural computations in the primary visual cortex (V1) can be partially modelled by sparse dictionary learning. By minimizing the regularized representation error they derived an online algorithm, which learns Gabor ...
Tao Hu, Cengiz Pehlevan, D. Chklovskii
semanticscholar +1 more source
Symmetry adapted Assur decompositions [PDF]
, 2014 Assur graphs are a tool originally developed by mechanical engineers to decompose mechanisms for simpler analysis and synthesis. Recent work has connected these graphs to strongly directed graphs, and decompositions of the pinned rigidity matrix.
Nixon, Anthony +3 more
core +4 more sources
Decompositions of ideals of minors meeting a submatrix [PDF]
, 2015 We compute the primary decomposition of certain ideals generated by subsets of minors in a generic matrix or in a generic symmetric matrix, or subsets of Pfaffians in a generic skew-symmetric matrix.
Neuerburg, Kent M., Teitler, Zach
core +3 more sources
On symmetrizers in quantum matrix algebras
Russian Mathematical Surveys, 2023 In this note we are dealing with a particular class of quadratic algebras -- the so-called quantum matrix algebras. The well-known examples are the algebras of quantized functions on classical Lie groups (the RTT algebras). We consider the problem of constructing some projectors on homogenous components of such algebras, which are analogs of the usual ...
Gurevich, Dmitry +2 more
openaire +2 more sources
Universal K-matrix for quantum symmetric pairs [PDF]
Journal für die Reine und Angewandte Mathematik, 2015 Let {{\mathfrak{g}}} be a symmetrizable Kac–Moody algebra and let
M. Balagovic, S. Kolb
semanticscholar +1 more source
The symmetric linear matrix equation [PDF]
The Electronic Journal of Linear Algebra, 2002 The authors study solutions to the equations \[ X \pm (A_1^*XA_1 +\ldots + A_m^*XA_m) =Q \] which occur in the Newton method applied to algebraic Riccati equations. Conditions are found for these equations to have unique solutions, and an explicit formula is given in the case when there is a unique positive definite solution.
Martine C.B. Reurings, André C. M. Ran
openaire +3 more sources
On the permanent of a random symmetric matrix [PDF]
Selecta Mathematica, 2021 Let $M_{n}$ denote a random symmetric $n\times n$ matrix, whose entries on and above the diagonal are i.i.d. Rademacher random variables (taking values $\pm 1$ with probability $1/2$ each). Resolving a conjecture of Vu, we prove that the permanent of $M_{n}$ has magnitude $n^{n/2+o(n)}$ with probability $1-o(1)$. Our result can also be extended to more
Kwan, Matthew, Sauermann, Lisa
openaire +2 more sources
Efficient and Non-Convex Coordinate Descent for Symmetric Nonnegative Matrix Factorization [PDF]
IEEE Transactions on Signal Processing, 2015 Given a symmetric nonnegative matrix A, symmetric nonnegative matrix factorization (symNMF) is the problem of finding a nonnegative matrix H, usually with much fewer columns than A, such that A ≈ HHT.
A. Vandaele +4 more
semanticscholar +1 more source