Efficiently computes option pricing matrix exponentials.
problem Computing matrix exponentials of nested block triangular matrices.
method Incremental computation using scaling and squaring, reusing intermediate quantities.
result Efficiently computes option pricing matrix exponentials.
Computes isotropy subgroups of orthogonal matrices acting on Hermitian matrices.
problem Computing isotropy subgroups of orthogonal matrices acting on Hermitian matrices.
method Algorithm for solving a matrix equation to compute isotropy subgroups.
result Computed isotropy subgroups of orthogonal matrices acting on Hermitian matrices.
Algorithm finds isotropy subgroups of orthogonal similarity on symmetric matrices.
problem Computing isotropy subgroups of orthogonal similarity on symmetric matrices.
method Algorithmic procedure solving a Toeplitz matrix equation.
result Structure of isotropy subgroups described.
We consider the problem of approximate joint triangularization of a set of noisy jointly diagonalizable real matrices. Approximate joint triangularizers are commonly used in the estimation of the joint eigenstructure of a set of matrices, with applications in signal processing, linear algebra, and tensor decomposition.…
New method for conditional sampling using M-GANs, likely-free inference.
problem Conditional sampling of probability measures.
method Developed a novel computational approach called M-GANs based on block triangular transport.
result Accurate sampling of conditional measures in various applications.
In this paper we look for closed expressions to calculate the number of colourings of prime knots for given linear Alexander quandles. For this purpose the colouring matrices are simplified to a triangular form, when possible. The operations used to perform this triangularization preserve the property that the entries …
Study reveals hidden structure behind Racah matrices for twisted knots.
problem Understanding non-associativity in representation products of twisted knots.
method Analysis of quantum R-matrices and their eigenvalues to decompose Racah matrices.
result Discovery of pentad structure (Tˉ,Sˉ,S,E,B) associated with universal R-matrix. The paper analyzes the observability of relative pose estimation using dual quaternions.
problem Estimating relative pose in robotics applications.
method Lie algebraic nonlinear observability analysis on a dual quaternion system.
result Dual quaternion representation yields an observability matrix with a simple block triangular structure and full rank.
Surface groups have solvable representations in SL(2,R).
problem Representing surface groups without simple loops.
method Torsion-free group of upper-triangular matrices in SL(2,R).
result No simple loop in the kernel of representations.
Reformulates Fock-Rosly Poisson structure using quasi-triangular r-matrices.
problem Defining Fock-Rosly Poisson structure on moduli spaces.
method Using Lie algebra actions and quasi-triangular r-matrices.
result Shows Fock-Rosly structure as mixed product Poisson structure.
It is known, since works of Burde and de Rham, that one can detect the roots of the Alexander polynomial of a knot by the study of the representations of the knot group into the group of the invertible upper triangular 2x2 matrices. In this work, we propose to generalize this result by considering the representations…
Researchers compute the cohomology ring of a foliation defined by a group action.
problem Computing the cohomology ring of a specific foliation defined by a group action.
method Non-abelian harmonic analysis on G to compute the leafwise cohomology ring. result Computed the leafwise cohomology ring H∗(FP). Triangular flows ensure statistical consistency and fast rates in generative modeling.
problem Ensuring statistical consistency and fast rates in generative models.
method Statistical guarantees and sample complexity bounds for triangular flow models using empirical process theory.
result Established statistical consistency and finite sample convergence rates for Kullback-Leibler estimator of Knöthe-Rosenblatt measure coupling.
Study finds conditions for operator fields to be in strictly upper triangular form in small dimensions.
problem Jordan-Chevalley decomposition for operator fields in small dimensions.
method Tensorial conditions and proof of conjecture for higher order brackets.
result Proves Tempesta-Tondo conjecture for higher order brackets.
We simplify matrix computations for block matrices, especially useful for covariance and correlation matrices.
problem Complex computations for block matrices, especially for covariance and correlation matrices.
method Obtained a canonical representation for block matrices, facilitating computation of various matrix operations.
result Simplified computation of matrix operations for block matrices, particularly useful for covariance and correlation matrices.
Smooth resolutions found for quotient of R^2 by infinite discrete groups.
problem Symplectic resolutions of quotient spaces by infinite discrete subgroups.
method Constructing smooth symplectic resolutions for R^2 under infinite discrete subgroups of GL_2(R).
result Minimal resolutions of Du Val singular varieties are symplectic resolutions of R^2/G.
Study isotropy groups for complex orthogonal and skew-symmetric matrices.
problem Understanding isotropy subgroups of orthogonal similarity transformations.
method Analysis of group structure of nonsingular block matrices.
result Group structure of isotropy subgroups related to block Toeplitz matrices.
The paper defines projective structures for Lie bialgebras and Poisson-Lie groups.
problem Defining projective analogues of Lie bialgebras and Poisson-Lie groups.
method Introducing projective tensor products and adapting classical notions to these structures.
result Every quasi-triangular projective r-matrix gives rise to a projective Banach Lie bialgebra.
Sharp pseudospectral bounds prevent transient amplification in coupled gradient descent.
problem Transient amplification in coupled gradient descent systems.
method Developed a sharp pseudospectral theory for block-triangular Jacobians, proving Kreiss constant bounds and matching minimax lower bounds.
result Obtained a finite-horizon iteration-complexity bound of O(K(J)2log(1/δ)) for stochastic coupled descent. Develops theory for conditional optimal transport in infinite-dimensional spaces.
problem Bayesian inference with functional parameters in infinite-dimensional spaces.
method Theory of constrained optimal transport for block-triangular maps.
result Regularity estimates on conditioning maps from prior to posterior.
This paper explores the relationship between Leibniz algebras and Nijenhuis operators.
problem Understanding the relationship between Leibniz algebras and Nijenhuis operators.
method Investigation of Nijenhuis operators on Leibniz algebras and classification of Leibniz bialgebras.
result Leibniz algebras are closely related to Nijenhuis operators, and triangular symplectic Leibniz bialgebras possess Nijenhuis operators.
New formula simplifies evolution of twist knots and calculates Racah matrices for rectangular representations.
problem Simplifying evolution of twist knots and calculating Racah matrices for rectangular representations.
method Developed a universal formula for triangular evolution matrix B applicable to rectangular representations R=[rs]. Used skew characters and Macdonald polynomials. result Explicit knowledge of twist-family evolution leads to a nearly explicit answer for Racah matrix Sˉ in arbitrary rectangular representation R. HINT improves invertible neural networks for better density estimation and Bayesian inference.
problem Sparse Jacobians limit expressiveness in invertible neural architectures.
method Recursive hierarchical coupling within subsets of variables leads to dense, triangular Jacobian.
result HINT allows efficient sampling from joint and posterior distributions using a single network.
Paper solves a key problem in learning from high-dimensional covariance matrices.
problem Computing normalizing factors for Riemannian Gaussian distributions on high-dimensional covariance matrices.
method Equivalence with random matrix theory and log-normal matrix ensembles to approximate normalizing factors.
result Efficient approximation of normalizing factors with decreasing error as dimension increases.
Researchers developed a new Riemannian manifold for SPD matrix-valued optimal transport problems.
problem Optimal transport between SPD matrix-valued measures.
method Formulated as a generalized optimal transport problem with block SPD matrices, endowed with a novel Riemannian manifold structure.
result The novel Riemannian manifold allows solving SPD matrix-valued optimal transport problems using Riemannian optimization.
New algorithm detects block-exchangeable structure in large correlation matrices.
problem Detecting hidden dependence patterns in large correlation matrices.
method Robust algorithm based on Kendall's rank correlation.
result The new estimator performs better than sample correlation matrices in structured cases.
Homogeneous links were introduced by Peter Cromwell, who proved that the projection surface of these links, that given by the Seifert algorithm, has minimal genus. Here we provide a different proof, with a geometric rather than combinatorial flavor. To do this, we first show a direct relation between the Seifert matrix…
The paper uses deep learning to detect financial market regimes from correlation matrices.
problem Detecting financial market regimes from correlation dynamics.
method Representation learning on block hierarchical SPD correlation matrices using SPDNet, SPD-NetBN, and U-SPDNet models.
result Deep learning models overfit in financial market data, misleading performance metrics.
Two algorithms estimate Wasserstein distance matrices from few entries for manifold learning.
problem Estimating Wasserstein distance matrices from limited data for manifold learning.
method Proposes two algorithms: matrix completion and Nyström completion for square Wasserstein matrices.
result Nyström completion can outperform matrix completion with a fixed sample budget and improve classification stability.
Develops a fast BMF approach for binary matrices.
problem Finding patterns in binary matrices for various applications.
method MEBF (Median Expansion for Boolean Factorization) using geometric segmentation and heuristic submatrix identification.
result Superior performance in reconstruction error and computational efficiency compared to existing methods.
Graph connection Laplacian (GCL) is a modern data analysis technique that is starting to be applied for the analysis of high dimensional and massive datasets. Motivated by this technique, we study matrices that are akin to the ones appearing in the null case of GCL, i.e the case where there is no structure in the datas…
This paper tackles fitting multilevel low rank matrices by addressing three problems.
problem Fitting a given matrix by an MLR matrix in the Frobenius norm.
method Factor fitting, rank allocation, and hierarchical partitioning.
result The proposed methods can fit a given matrix by an MLR matrix in the Frobenius norm.
We give a direct interpretation of Neumann's combinatorial formula for the Chern-Simons invariant of a 3-manifold with a representation in PSL(2,C) whose restriction to the boundary takes values in upper triangular matrices. Our construction does not involve group homology or Bloch group but is based on the constructio…
The paper reduces the complexity of financial market correlation matrices to a 2x2 matrix.
problem Reducing the complexity of financial market correlation matrices for easier analysis.
method Sectorial coarse graining followed by averaging over blocks of stocks.
result Averaging over blocks of stocks results in a reduced matrix with specific properties.
New estimators reduce computation for Kendall's tau and conditional Kendall's tau matrices under structural assumptions.
problem Efficient estimation of Kendall's tau and conditional Kendall's tau matrices for large dimensions.
method Averaging pairwise estimates over blocks or conditional estimates, exploiting structural assumptions.
result Improved estimators with reduced computational cost and similar error level.
Modular method simplifies curvature computation in neural nets.
problem Efficient computation of curvature matrices for training neural nets.
method Modular backpropagation for block-diagonal approximations.
result Compact notation and easy integration into machine learning libraries.
New Riemannian metric for SPD matrices avoids swelling effect.
problem Efficiency and stability in computing with SPD matrices.
method Log-Cholesky decomposition and Lie group structure.
result Log-Cholesky average maintains determinant bounds.
This paper solves matrix blind joint block diagonalization with noise.
problem Identifying the diagonalizer and block diagonal structure of matrices under noise.
method Bi-block diagonalization method.
result The method can identify the exact solution under certain conditions.
Introduces BMF for efficient matrix factorization of large data.
problem Efficiently factorizing large scale matrices with limited memory.
method Uses block matrix approach and factorization at a block level.
result Demonstrates faster convergence on large matrices.
Proves conjecture linking WRT invariants and homological blocks for plumbed 3-manifolds.
problem Proving a conjecture about Witten-Reshetikhin-Turaev invariants and homological blocks for plumbed 3-manifolds.
method Developed a new technique for asymptotic expansions to compare WRT invariants and homological blocks, proving vanishing of weighted Gauss sums.
result Proved conjecture stating WRT invariants are radial limits of homological blocks.
New method classifies special Vinberg cones of rank 4.
problem Classifying special Vinberg cones of rank 4.
method Using Clifford Nil-algebras and directed acyclic graphs.
result Explicit classification of rank 4 special Vinberg cones.
We study the de Rham 1-cohomology H^1_{DR}(M,G) of a smooth manifold M with values in a Lie group G. By definition, this is the quotient of the set of flat connections in the trivial principle bundle M×G by the so-called gauge equivalence. We consider the case when M is a compact Kähler manifold and G is a solv…
Let T be the nilpotent group of 4 x 4 real upper triangular matrices. In this note we show that the Euler equations of certain left-invariant riemannian metrics on T have a horseshoe. We also show, with the aid of a numerical computation of a Melnikov-type integral, that the Euler equations of the sub-riemannian Carnot…
Paper presents a new triangular form for flat systems.
problem Designing flat systems with two inputs.
method Geometric characterization and static feedback equivalence.
result Sufficient condition for affine input systems to be flat.
Proposes BONMI for integrating noisy matrices from multi-source data.
problem Integrating noisy matrices from multi-source data with block-wise missingness.
method Exploits orthogonal Procrustes problem to align eigenspaces and completes missing blocks.
result Statistical rate for eigenspace of underlying matrix comparable to independently missing assumption.
Enhanced EEG classification improves motor imagery detection with less computation.
problem Improving classification accuracy of motor imagery EEG signals.
method Integrates Block-Toeplitz structure into augmented covariance matrices and uses Siegel metric.
result Significantly reduces computational time without compromising classification accuracy.
New algorithm approximates large matrices by sampling column blocks, reducing overhead.
problem Approximating large matrices using limited row or column sampling.
method Sampling predefined blocks of columns, providing guarantees for approximation quality.
result Effective algorithm for distributed matrix approximation, demonstrated with real-world biometric data.
Paper presents a new flat triangular form for systems.
problem Creating a structurally flat triangular form for systems.
method Developed a new triangular form based on the extended chained form with conditions for static feedback equivalence.
result Provided conditions for affine input systems to be static feedback equivalent to the new triangular form.