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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.

168,742 papers · 148 categories

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6491,2971,9462,594 · Jun 202019922001200920172026
48 results for units of measurement

Study examines how business units can benefit from group cohesion under regulatory constraints.

problem Regulatory constraints limit business units' ability to form a single cohesive group.
method Defined and analyzed cohesive risk measures to minimize capital costs.
result Cohesive risk measures allow groups to achieve minimal capital costs without altering individual liabilities.

Volume of unit balls defined by quadratic differentials is not proper and has integrable volume.

problem Characterizing the behavior of volume functions associated with quadratic differentials.
method Analyzing the Thurston volume of unit balls in measured lamination spaces.
result The volume function is not proper and is pp-integrable for any 0<p<10<p<1.

We present a new blow-up method that allows for establishing the first general formula to compute the perimeter measure with respect to the spherical Hausdorff measure in noncommutative nilpotent groups. This result leads us to an unexpected relationship between the area formula with respect to a distance and the profi…

2014-08-20abs ↗pdf ↗

Geodesics of the same type on curved surfaces are randomly distributed.

problem Distribution of geodesics of the same type on negatively curved surfaces.
method Asymptotic equidistribution with respect to a measure on the unit tangent bundle.
result Geodesics of the same type are asymptotically equidistributed with respect to a measure mS\mathfrak{m}^S.

Potential Future Exposure (PFE) is a standard risk metric for managing business unit counterparty credit risk but there is debate on how it should be calculated. The debate has been whether to use one of many historical ("physical") measures (one per calibration setup), or one of many risk-neutral measures (one per num…

2015-12-19abs ↗pdf ↗

The paper studies properties of RCD(K,N)\mathrm{RCD}(K,N) spaces and their boundaries.

problem Understanding the boundary structure and unit normal on RCD(K,N)\mathrm{RCD}(K,N) spaces.
method Proves concentration of boundary measure, discusses localization of unit normal, and develops tools for perimeter minimizers.
result Proves that the boundary measure of sets with finite perimeter is concentrated on the nn-regular set Rn\mathcal{R}_n.

We give a short proof of the fact that bounded earthquakes of the unit disk induce quasisymmetric maps of the unit circle. By a similar method, we show that symmetric maps are induced by bounded earthquakes with asymptotically trivial measures.

2006-10-10abs ↗pdf ↗

Paper derives Thiele's equation for unit-linked policies in a stochastic volatility model.

problem Deriving pricing formula for unit-linked policies in a stochastic volatility model.
method Derives Thiele's differential equation for a unit-linked policy in the Heston-Hawkes model.
result Established a method to compute reserves in life insurance via solving Thiele's equation.

The paper studies the geometry of probability measures on the unit circle.

problem Understanding the Riemannian geometry of probability measures on the unit circle.
method Developed an intrinsic framework using the Peter-Weyl Theorem to study the differential geometry of Wasserstein spaces of compact Lie groups.
result Explicitly demonstrated that the Wasserstein space of the unit circle is flat with vanishing curvature.

New method reduces overfitting in deep neural networks by measuring and regulating hidden unit diversity.

problem Overfitting in deep neural networks.
method Introduces a new redundancy measure based on mutual information to improve generalization.
result Reduction of redundancy improves generalization capacity, reducing overfitting.

We study the generic invariant probability measures for the geodesic flow on connected complete nonpositively curved manifolds. Under a mild technical assumption, we prove that ergodicity is a generic property in the set of probability measures defined on the unit tangent bundle of the manifold and supported by traject…

2014-01-21abs ↗pdf ↗

Deep belief networks can approximate any multivariate density with binary hidden units.

problem Approximating multivariate probability densities with binary hidden units.
method Sharp quantitative bounds on approximation error in terms of hidden units.
result Deep belief networks can approximate any multivariate density with binary hidden units under mild integrability requirements.

The paper solves a new Minkowski problem involving convex bodies and curvature measures.

problem Finding convex bodies with specific curvature measures.
method Solving Monge-Ampère type equations using variational and Gaussian curvature flow methods.
result Existence and uniqueness of solutions for the LpL_p-Gauss dual Minkowski problem.

We show that for any weakly convergent sequence of ergodic SL2(R)SL_2(\mathbb{R})-invariant probability measures on a stratum of unit-area translation surfaces, the corresponding Siegel-Veech constants converge to the Siegel-Veech constant of the limit measure. Together with a measure equidistribution result due to Eskin-M…

2016-12-31abs ↗pdf ↗

New combinatorial structures for Teichmüller spaces with Thurston's metric are explored.

problem Understanding the combinatorial structures of Teichmüller spaces with Thurston's metric.
method Analyzing the unit tangent and cotangent spheres of Teichmüller space, proving formulas for dimensions and codimensions of faces.
result The combinatorial structure of unit spheres in Teichmüller spaces is independent of the underlying point and is isomorphic to the extended mapping class group.

This work tackles the problem of learning a set of language specific acoustic units from unlabeled speech recordings given a set of labeled recordings from other languages. Our approach may be described by the following two steps procedure: first the model learns the notion of acoustic units from the labelled data and …

2019-04-08abs ↗pdf ↗

A method for making machine learning units-equivariant using dimensional analysis.

problem Ensuring machine learning models respect dimensional consistency.
method Constructing dimensionless inputs and applying equivariant machine learning methods.
result Improved accuracy in tasks requiring dimensional consistency.

Let Gamma be a non-elementary Kleinian group acting on the closed n-dimensional unit ball and assume that its Poincare series converges at the exponent alpha. Let M_Gamma be the Gamma-quotient of the open unit ball. We consider certain families E = {E_1,...,E_p} of open subsets of M_Gamma such that M_Gamma minus the un…

2004-09-29abs ↗pdf ↗

The Thurston norm of a 3-manifold measures the complexity of surfaces representing two-dimensional homology classes. We study the possible unit balls of Thurston norms of 3-manifolds MM with b1(M)=2b_1(M) = 2, and whose fundamental groups admit presentations with two generators and one relator. We show that even among this…

2018-03-14abs ↗pdf ↗

Estimates missing distributions using nearest neighbors with kernel methods.

problem Missing data and unobserved confounding in multivariate distributions.
method Distributional matrix completion framework with kernel nearest neighbors.
result Consistent recovery of underlying distributions with missing data.

Improved statistical inference for expensive data using machine learning predictions.

problem Statistical inference under adaptive two-phase multiwave sampling with expensive measurements.
method Multiwave Predict-Then-Debias estimator combining proxy information and expensive measurements.
result Valid estimators and confidence intervals for M-estimation under adaptive sampling.

Training data-driven approaches for complex industrial system health monitoring is challenging. When data on faulty conditions are rare or not available, the training has to be performed in a unsupervised manner. In addition, when the observation period, used for training, is kept short, to be able to monitor the syste…

2019-07-15abs ↗pdf ↗

The existence of kinematic formulas for area measures with respect to any connected, closed subgroup of the orthogonal group acting transitively on the unit sphere is established. In particular, the kinematic operator for area measures is shown to have the structure of a co-product. In the case of the unitary group the…

2013-08-28abs ↗pdf ↗

We prove that the flat product metric on Dn×S1D^n\times S^1 is scattering rigid where DnD^n is the unit ball in Rn\R^n and n2n\geq 2. The scattering data (loosely speaking) of a Riemannian manifold with boundary is map S:U+MUMS:U^+\partial M\to U^-\partial M from unit vectors VV at the boundary that point inward to unit vecto…

2011-03-28abs ↗pdf ↗

Geodesics in curved spaces spread evenly over time.

problem Equidistribution of geodesics in negatively curved spaces.
method Proving equidistribution of geodesic flow orbits towards measures of maximal entropy and Bowen-Margulis measure.
result Equidistribution of divergent geodesics in negative curvature as their complexity increases.

Analyzes convex structures in Teichmüller space unit tangent spheres.

problem Characterize faces and extreme points of unit tangent spheres in Teichmüller space.
method Analyzes Finsler infinitesimal balls of Thurston metric, characterizes faces, exposed faces, and extreme points.
result Characterizes faces and extreme points of unit tangent spheres in Teichmüller space.

For convex co-compact hyperbolic manifolds Γ\Hn+1Γ\backslash \mathbb{H}^{n+1} for which the dimension of the limit set satisfies δΓ<n/2δ_Γ< n/2, we show that the high-frequency Eisenstein series associated to a point ξξ "at infinity" concentrate microlocally on a measure supported by (the closure of) the set of points in the …

2011-07-13abs ↗pdf ↗

Synthetic control method improves policy evaluation in high-dimensional settings.

problem Evaluating the impact of new policies in large-scale applications.
method Two-phase approach: nearest neighbor matching followed by supervised learning.
result The method successfully improves estimate accuracy in large-scale experiments.