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arXiv research

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.

169,051 papers · 148 categories

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12.5%25.0%37.5%50.0% · Sep 199319922001200920182026
48 results for Mackey correspondence

Generalizes CNNs on homogeneous spaces like Euclidean and spherical surfaces.

problem Classifying and understanding equivariant CNNs on homogeneous spaces.
method Develops a theory for equivariant maps between field spaces of given types.
result Equivariant kernels correspond to the most general kind of equivariant linear maps.

New map constructed from equivariant spectra for manifold study.

problem Understanding equivariant parametrized h-cobordism in non-manifold settings.
method Constructed a map from suspension G-spectrum to equivariant A-theory spectrum, compatible with tom Dieck splitting formulas.
result Fiber of constructed map is wedge of stable h-cobordism spectra.

Mackey showed that for a compact Lie group KK, the pair (K,C0(K))(K,C^{0}(K)) has a unique non-trivial irreducible covariant pair of representations. We study the relevance of this result to the unitary equivalence of quantizations for an infinite-dimensional family of K×KK\times K invariant polarizations on TKT^{\ast}K. The …

2012-11-09abs ↗pdf ↗

RPNN-EOFs model improves time series forecasting accuracy.

problem Improving time series forecasting accuracy for complex systems.
method Combines higher-order neural networks with error-output feedbacks.
result RPNN-EOFs outperformed other models in forecasting the Mackey-Glass time series.

Study on diffeologies on locally convex spaces and smooth multiplication of distributions.

problem Geometric characterization and smoothness of distribution multiplication.
method Investigation of canonical and cc^\infty-diffeologies on locally convex spaces, proving geometric characterizations, and comparing diffeologies.
result Established a framework for nonlinear distribution theory beyond manifolds, realizing microlocally multipliable distributions as a diffeological colimit.

Functor connects Lie groupoid algebras to bornological structures.

problem Establishing a functorial relationship between Lie groupoid convolution algebras and bornological structures.
method Developed a monoidal functor from differentiable stacks to Morita 2-category of complete bornological algebras.
result Convolution algebras are self-induced and convolution modules are smooth.

We construct for an equivariant cohomology theory for proper equivariant CW-complexes an equivariant Chern character, provided that certain conditions about the coefficients are satisfied. These conditions are fulfilled if the coefficients of the equivariant cohomology theory possess a Mackey structure. Such a structur…

2004-01-06abs ↗pdf ↗

We solve the regularity problem for Milnor's infinite dimensional Lie groups in the C0C^0-topological context, and provide necessary and sufficient regularity conditions for the (standard) CkC^k-topological setting. We prove that the evolution map is C0C^0-continuous on its domain iff\textit{iff}\hspace{1pt} the Lie gro…

2017-11-09abs ↗pdf ↗

We solve the regularity problem for Milnor's infinite dimensional Lie groups in the asymptotic estimate context. Specifically, let GG be a Lie group with asymptotic estimate Lie algebra g\mathfrak{g}, and denote its evolution map by evol ⁣:Ddom[evol]G\mathrm{evol}\colon \mathrm{D}\equiv \mathrm{dom}[\mathrm{evol}]\rightarrow G, i.e.…

2018-04-29abs ↗pdf ↗

Extends particle classification to curved space-times using groupoids.

problem Classifying elementary particles in curved space-time.
method Developed a new definition of elementary particles as irreducible projective representations of kinematical groupoids, extending Wigner's program.
result Classification of elementary particles valid for a wide range of space-times, including new massless particles in magnetic-like backgrounds.

Combines Fourier methods and RNNs for efficient time series prediction.

problem Efficiently processing and predicting time series data with memory and computational constraints.
method Uses short-time Fourier transform and weight reductions through low pass filtering in a Spectral RNN.
result Predicts time series data from chaotic systems and real-world data.

In the dual LΦL_{Φ^*} of a Δ2Δ_2-Orlicz space LΦL_Φ, that we call a dual Orlicz space, we show that a proper (resp. finite) convex function is lower semicontinuous (resp. continuous) for the Mackey topology τ(LΦ,LΦ)τ(L_{Φ^*},L_Φ) if and only if on each order interval [ζ,ζ]={ξ:ζξζ}[-ζ,ζ]=\{ξ: -ζ\leq ξ\leqζ\} (ζLΦζ\in L_{Φ^*}), it is lowe…

2016-11-18abs ↗pdf ↗

Improved convergence rates for Stein Variational Gradient Descent in finite-particle settings.

problem Improving convergence rates for Stein Variational Gradient Descent in finite-particle settings.
method Analyzing the time derivative of relative entropy and splitting it into dominant and smaller parts.
result Finite-particle convergence rates of order 1/\sqrt{N} for Kernelized Stein Discrepancy and Wasserstein-2 metrics.

Counterexample disproves completeness of model space forcing regularity in infinite-dimensional Lie groups.

problem Whether every Lie group modeled on a complete locally convex space is regular.
method Constructing a specific contractible complex analytic BCH-Lie group with unique properties.
result The group is not even C0C^0-semiregular, and smooth controls have no C1C^1 evolution.

We study diffeologies on locally convex spaces and their application to smooth multiplication of distributions.

problem Constructing smooth multiplication of distributions on locally convex spaces.
method Using diffeological colimits and wavefront-set criterion.
result Proving smooth multiplication of microlocally multipliable distributions.

ICA accurately estimates treatment effects even with confounders.

problem Estimating treatment effects in the presence of confounding variables.
method Uses Independent Component Analysis (ICA) to identify latent sources and estimate mixing coefficients.
result Linear ICA can consistently estimate multiple treatment effects, even with Gaussian confounders, and is more sample-efficient than Orthogonal Machine Learning (OML).

ForGAN uses GANs for probabilistic forecasting of sensory data.

problem Challenges in traditional forecasting methods and difficulties in probabilistic methods.
method ForGAN combines GANs with conditional generative adversarial networks to learn data distributions and generate probabilistic forecasts.
result ForGAN outperforms traditional regression methods in probabilistic forecasting of sensory data.

Characterizes continuity of monotone functionals in mixed topology.

problem Continuity of monotone functionals in mixed topology.
method Characterization through lower semicontinuity and dual representations.
result Continuity in mixed topology is equivalent to dual representation in terms of countably additive measures.

Compress++ speeds up distribution compression to near-linear time.

problem Accurately summarize a probability distribution using a small number of points efficiently.
method Introduces Compress++, a meta-procedure to speed up any thinning algorithm.
result Achieves n\sqrt{n} points with O(logn/n)\mathcal{O}(\sqrt{\log n/n}) integration error in O(nlog3n)\mathcal{O}(n \log^3 n) time and O(nlog2n)\mathcal{O}( \sqrt{n} \log^2 n ) space.

Global models outperform univariate benchmarks in complex time series forecasting.

problem Comparing global forecasting models to univariate benchmarks in various challenging scenarios.
method Simulated datasets with controlled characteristics, including homogeneity, complexity, and series lengths. Global forecasting models (RNN, LGBM) compared to univariate techniques.
result Global models like RNN and LGBM are competitive in complex scenarios with short series lengths and heterogeneous data.

Enhanced fuzzy system predicts chaotic time series with improved accuracy.

problem Forecasting chaotic time series with high uncertainty.
method Combines evolving fuzzy systems, participatory learning, KRLS, and type-2 fuzzy sets.
result Proposed model outperforms other methods in accuracy and complexity.

Base of fibered correspondence is arbitrary correspondence. Fibered correspondence is interesting when we consider relationship between different bundles. However composition of fibered correspondences may not always be defined. Reduced fibered correspondence is defined only between fibers over the same point of base. …

2007-07-16abs ↗pdf ↗

Study of holomorphic correspondences combining entire maps and Fuchsian groups.

problem Understanding dynamics of entire maps and their interactions with Fuchsian groups.
method Systematic study of (:)(\infty : \infty) holomorphic correspondences arising from conformal combinations of transcendental entire maps and Fuchsian groups.
result The resulting correspondence is the composition of a Möbius involution and the deleted covering correspondence of a meromorphic function with a simple pole.

New geometric proof for rational tangles links-quivers correspondence.

problem Recovering symmetric/antisymmetric colored HOMFLY-PT polynomials from a quiver.
method Geometric approach using winding numbers in punctured plane and its second configuration space.
result Explicit description of quivers for rational tangles.

The paper defines a category of Lagrangian correspondences in super Hilbert spaces and constructs a functorial field theory.

problem Understanding composition of Lagrangian correspondences in Hilbert spaces.
method Study of Lagrangian correspondences, construction of a category, and functorial field theory.
result Well-defined composition law in a category of Lagrangian correspondences.

Constructs correspondences on hyperelliptic surfaces combining orbifold groups and Blaschke products.

problem Combining geometric and dynamical properties on hyperelliptic surfaces.
method Analytic combinations on Riemann sphere, algebraic characterization, and Teichmüller spaces.
result Explicit description of correspondences and injection into Hurwitz spaces.

The calculus correspondence has been known to exist between generic pedal evolutions and generic wave front evolutions. In this paper, we first extend the known results on the calculus correspondence to evolutions with multi-parameters, and then give applications of calculus correspondence. Moreover, we discuss the pos…

2012-06-25abs ↗pdf ↗

Study Kobayashi-Hitchin correspondence for special sheaves on Kähler manifolds.

problem Understanding the Kobayashi-Hitchin correspondence for specific sheaves.
method Using Hermitian-Yang-Mills flow on Kähler manifolds with simple normal crossing divisors.
result Established the correspondence for saturated reflexive parabolic sheaves.

Constructs Lagrangian correspondences for Higgs bundles and holomorphic connections.

problem Realizing geometric Langlands correspondences for Higgs bundles and connections.
method Using transversal Higgs bundles and holomorphic connections, induced divisors and parameters.
result Evidence suggests generic realization of Dolbeault geometric Langlands correspondence.

The paper extends Riemann-Hilbert correspondence to foliations.

problem Understanding representations of Lie algebroids and groupoids in foliated settings.
method Establishing an AA_{\infty} de Rham theorem and constructing an integration functor.
result An equivalence between \infty-representations of LL_{\infty}-algebroids and \infty-representations of Lie \infty-groupoids for foliations.

ROBOT framework solves regression without correspondence for large data and complex models.

problem Regression without known correspondence in large datasets.
method ROBOT framework reformulates regression as a continuous optimization problem and uses hypergradient approach.
result ROBOT achieves better performance than existing methods in linear and nonlinear regression tasks.