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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,291 papers · 148 categories

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3570105140 · Jun 202019922001200920182026
48 results for kernel k-groups

Kernel k-Groups uses Hartigan's method for clustering in metric spaces of negative type.

problem Clustering in metric spaces of negative type.
method Weighted energy statistics, quadratically constrained quadratic program, kernel k-groups, Hartigan's method.
result Improved performance in higher dimensions compared to spectral clustering and kernel k-means.

The paper studies topological indices of geometric operators on manifolds with fibered boundaries.

problem Investigating indices of geometric operators on manifolds with fibered boundaries.
method Defining K-groups relative to pushforward for boundary fibration, using groupoid deformation techniques to prove properties of indices.
result Indices of twisted geometric operators can be understood as index pairings over K-groups.

Let Z be a smooth projective manifold. In these notes I will prove that the K-group of R-constructible sheaves is isomorphic to the free abelian group with one generator for each open semialgebraic subset UU (which I will denote by the same letter) modulo the Mayer-Vietoris relations: U + V - U^V - UvV = 0. I will pro…

2002-09-04abs ↗pdf ↗

Researchers solve word and conjugacy problems for a specific group family.

problem Word and conjugacy problems in groups Gk+1kG_{k+1}^k.
method Construction of invariants and topological invariants.
result Word and conjugacy problems for certain Gk+1kG_{k+1}^k groups are algorithmically solvable.

We give an infinite dimensional description of the differential K-theory of a manifold MM. The generators are triples [H,A,ω][H, A, ω] where HH is a Z2{\bf Z}_2-graded Hilbert bundle on MM, AA is a superconnection on HH and ωω is a differential form on MM. The relations involve eta forms. We show that the ensuing gro…

2015-12-22abs ↗pdf ↗

For an orbifold X and αH3(X,Z)α\in H^3(X, Z), we introduce the twisted cohomology Hc(X,α)H^*_c(X, α) and prove that the Connes-Chern character establishes an isomorphism between the twisted K-groups Kα(X)CK_α^* (X) \otimes C and twisted cohomology Hc(X,α)H^*_c(X, α). This theorem, on the one hand, generalizes a classical result of Baum-Co…

2005-05-12abs ↗pdf ↗

Study of groups GnkG_n^k and ΓnkΓ_n^k connects particle dynamics to manifold triangulations.

problem Understanding the relationship between particle dynamics and manifold triangulations.
method Introducing and studying groups GnkG_n^k and ΓnkΓ_n^k to connect dynamical systems to topological invariants.
result Found a topological invariant valued in GnkG_{n}^{k} for dynamical systems.

For a continuous curve of families of Dirac type operators we define a higher spectral flow as a KK-group element. We show that this higher spectral flow can be computed analytically by $\heta$-forms, and is related to the family index in the same way as the spectral flow is related to the index. We introduce a notion…

1996-08-08abs ↗pdf ↗

In this paper we show that the fibered isomorphism conjecture of Farrell and Jones corresponding to the stable topological pseudoisotopy functor is true for the fundamental groups of a large class of complex manifolds. A consequence of this result is that the Whitehead group, reduced projective class groups and the neg…

2002-09-11abs ↗pdf ↗

The goal of the present paper is the calculation of the equivariant twisted K-theory of a compact Lie group which acts on itself by conjugations, and elements of a TQFT-structure on the twisted K-groups. These results are originally due to D.S.Freed, M.J.Hopkins and C.Teleman. In this paper we redo their calculations i…

2005-04-22abs ↗pdf ↗

A families index theorem in K-theory is given for the setting of Atiyah, Patodi and Singer of a family of Dirac operators with spectral boundary condition. This result is deduced from such a K-theory index theorem for the calculus of cusp, or more generally fibred cusp, pseudodifferential operators on the fibres (with …

2005-07-28abs ↗pdf ↗

Syncytial clustering merges groups from standard algorithms to reveal complex data structures.

problem Challenges in finding clusters with irregular structures.
method Estimates nonparametric overlap between clusters and merges groups with high overlap.
result Always a top performer in identifying groups with regular and irregular structures.

We establish the Thom isomorphism in twisted K-theory for any real vector bundle and develop the push-forward map in twisted K-theory for any differentiable proper map f:XYf: X\to Y (not necessarily K-oriented). The push-forward map generalizes the push-forward map in ordinary K-theory for any KK-oriented differentiable…

2005-07-21abs ↗pdf ↗

For a finite volume geodesic polyhedron P in hyperbolic 3-space, with the property that all interior angles between incident faces are integral submultiples of Pi, there is a naturally associated Coxeter group generated by reflections in the faces. Furthermore, this Coxeter group is a lattice inside the isometry group …

2009-04-01abs ↗pdf ↗

Paper proposes universally consistent K-sample tests using any dependence measure.

problem Testing whether K groups of data points are drawn from the same distribution.
method Demonstrates the use of any dependence measure for K-sample testing.
result Achieves universally consistent K-sample testing using distance correlation and Hilbert-Schmidt independence criterion.

In this paper, we develop twisted KK-theory for stacks, where the twisted class is given by an S1S^1-gerbe over the stack. General properties, including the Mayer-Vietoris property, Bott periodicity, and the product structure KαiKβjKα+βi+jK^i_α\otimes K^j_β\to K^{i+j}_{α+β} are derived. Our approach provides a uniform framework …

2003-06-08abs ↗pdf ↗

In this paper we develop analysis of the monopole maps over the universal covering space of a compact four manifold. We induce a property on local properness of the covering monopole map under the condition of closeness of the AHS complex. In particular we construct a higher degree of the covering monopole map when the…

2016-06-08abs ↗pdf ↗

One way to geometrically encode the singularities of a stratified pseudomanifold is to endow its interior with an iterated fibred cusp metric. For such a metric, we develop and study a pseudodifferential calculus generalizing the Φ-calculus of Mazzeo and Melrose. Our starting point is the observation, going back to Mel…

2011-12-20abs ↗pdf ↗

We ask if any finite type generalized braid group is a subgroup of some classical Artin braid group. We define a natural map from a given finite type generalized braid group to a classical braid group and ask if this map is an injective homomorphism. We prove that this map is a homomorphism for the braid groups of type…

2001-08-24abs ↗pdf ↗

The geometry of submanifolds is intimately related to the theory of functions and vector bundles. It has been of fundamental importance to find out how those two objects interact in many geometric and physical problems. A typical example of this relation is that the Picard group of line bundles on an algebraic manifold…

2000-10-02abs ↗pdf ↗

Constructs units in cyclotomic fields from Bloch groups, proving Nahm's conjecture.

problem Proving Nahm's conjecture relating modularity of qq-hypergeometric series to Bloch group elements.
method Uses Bloch groups, cyclic quantum dilogarithm, and K-theory to construct units.
result Proves Nahm's conjecture, connecting modularity to Bloch group elements.

New lower bounds show challenges in clustering in moderate dimensions.

problem Clustering points from mixtures of isotropic Gaussians in moderate dimensions.
method Established low-degree polynomial lower bounds and developed a novel non-spectral algorithm.
result New lower bounds reveal a 'non-parametric rate' in moderate dimensions.

New method uses neural networks for accurate angle estimation in noisy conditions.

problem Accurately estimate angles from noisy measurements in various applications.
method Directed Graph Neural Networks (GNNSync) for end-to-end trainable framework.
result GNNSync achieves competitive performance, even at high noise levels.

In string theory, the concept of T-duality between two principal U(1)-bundles E_1 and E_2 over the same base space B, together with cohomology classes h1H3(E1)h_1\in H^3(E_1) and h2H3(E2)h_2\in H^3(E_2), has been introduced. One of the main virtues of T-duality is that h1h_1-twisted K-theory of E1E_1 is isomorphic to h2h_2-twisted…

2004-05-07abs ↗pdf ↗

The paper defines K-theoretic secondary invariants for Lie groupoids and proves related index theorems.

problem Constructing secondary invariants for Lie groupoids and proving their properties.
method Lie groupoid version of constructions from Piazza and Schick, focusing on adiabatic deformations and geometric operators.
result Lie groupoid version of Delocalized APS Index Theorem and product formula for secondary invariants.

The paper describes the K-theory of CC^*-algebras of locally finite graphs.

problem Computing the K-theory of CC^*-algebras of locally finite graphs.
method Using a directed graph representation and Cuntz-Krieger algebra, the paper computes the K-theory of C(Γ)C^*(Γ).
result The K-theory of C(Γ)C^*(Γ) is determined by the graph's genus, number of ends, and dead-ends.

Study on a new family of problems interpolating expert advice and multi-armed bandits.

problem A new family of problems combining expert advice and multi-armed bandits.
method Proved minimax regret bounds and designed optimal PAC algorithms for pure exploration.
result Tight minimax regret bounds and optimal PAC algorithm for m\mathbf{m}-BAI.

FORCE efficiently solves complex clustering problems with guaranteed optimality.

problem Efficiently clustering variables or points into groups using SDP relaxations.
method Combines primal first-order method with dual optimality certificate search.
result Guaranteed to find optimal solution for certain variable clustering problems.

Robust kernel CCA method detects outliers and improves performance.

problem Kernel CO and CCO sensitivity to contaminated data.
method Proposed robust kernel CO and CCO, derived IF for CCA, robust kernel CCA method.
result Robust kernel CCA method performs better than standard kernel CCA for ideal and contaminated data.

Survey of kernels, RKHS, and their applications in machine learning.

problem Understanding kernels and their applications in machine learning.
method Review of historical context, mathematical definitions, and practical applications of kernels.
result Comprehensive overview of kernels, RKHS, and their applications.

Study on expressive power of Euclidean kernels and efficient kernel learning.

problem Limiting the expressive power of kernel methods and improving kernel learning efficiency.
method Define Euclidean kernels, analyze their geometric and spectral properties, and develop efficient algorithms for kernel learning.
result Prove limitations on the expressive power of Euclidean kernels and derive efficient algorithms for kernel learning.

Kernel methods linked to feature subspaces and maximal correlation kernels.

problem Understanding kernel methods and their relationship to feature extraction.
method Established a correspondence between feature subspaces and kernels, introduced maximal correlation kernels, and demonstrated their optimality.
result Kernel SVM on maximal correlation kernel achieves minimum prediction error.

Proposes a method to learn a low-rank kernel matrix for graph-based clustering.

problem Challenges in learning an optimal kernel matrix for graph-based clustering.
method Unified framework for graph construction and kernel learning, focusing on a low-rank kernel matrix.
result Efficacy of the proposed method validated through extensive experiments.

Quantum kernels can be efficiently embedded into classical feature spaces.

problem Can all quantum kernels be efficiently embedded into classical feature spaces?
method Invoking computational universality and using techniques like random Fourier features, the authors show that certain classes of quantum kernels can be efficiently embedded.
result For shift-invariant and composition kernels, embedding quantum kernels are universal and efficient.

New random feature maps for Laplacian and related kernels.

problem Challenges in approximating the Laplacian kernel and its generalizations.
method Developed random feature maps for Laplacian and related kernels, providing efficient sampling schemes.
result Demonstrated the efficacy of these random feature maps on real datasets.