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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.

168,742 papers · 148 categories

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48 results for Lamé coefficients

We assume a vector bundle p:EMp: E\to M with a general linear connection KK and a classical linear connection $\Lam$ on MM. We prove that all classical linear connections on the total space EE naturally given by $(\Lam, K)$ form a 15-parameter family. Further we prove that all connections on J1EJ^1 E naturally given by…

2004-10-21abs ↗pdf ↗

The paper expands cluster algebra formulae to non-orientable surfaces and proves positivity.

problem Proving positivity for quasi-cluster algebras from non-orientable surfaces.
method Generalizing Musiker, Schiffler, and Williams' expansion formulae to principal laminations and quasi-triangulations.
result Positivity for quasi-cluster algebras is proven with respect to any choice of coefficients.

Let SS be a closed orientable surface with genus g2g\geq 2. For a sequence $\s_i$ in the Teichmüller space of SS, which converges to a projective measured lamination $[\lam]$ in the Thurston boundary, we obtain a relation between $\lam$ and the geometric limit of pants decompositions whose lengths are uniformly bound…

2005-06-02abs ↗pdf ↗

We address the problem of {\it adaptivity} in the framework of reproducing kernel Hilbert space (RKHS) regression. More precisely, we analyze estimators arising from a linear regularization scheme $g_\lam$. In practical applications, an important task is to choose the regularization parameter $\lam$ appropriately, i.e.…

2018-04-15abs ↗pdf ↗

It was shown by Fomin, Shapiro and Thurston that some cluster algebras arise from orientable surfaces. Subsequently, Dupont and Palesi extended this construction to non-orientable surfaces. We link this framework to Lam and Pylyavskyy's Laurent phenomenon algebras, showing that both orientable and non-orientable unpunc…

2016-08-16abs ↗pdf ↗

We provide integral formulae for the ADM mass of asymptotically flat hypersurfaces in Riemannian manifolds with a certain warped product structure in a neighborhood of infinity, thus extending Lam's recent results on Euclidean graphs to this broader context. As applications we exhibit, in any dimension, new classes of …

2011-08-27abs ↗pdf ↗

The amplituhedra arise as images of the totally nonnegative Grassmannians by projections that are induced by linear maps. They were introduced in Physics by Arkani-Hamed \& Trnka (Journal of High Energy Physics, 2014) as model spaces that should provide a better understanding of the scattering amplitudes of quantum fie…

2018-06-03abs ↗pdf ↗

In this paper we study asymptotically hyperbolic manifolds given as graphs of asymptotically constant functions over hyperbolic space $\bH^n$. The graphs are considered as subsets of $\bH^{n+1}$ and carry the induced metric. For such manifolds the scalar curvature appears in the divergence of a 1-form involving the int…

2012-01-16abs ↗pdf ↗

The paper studies totally nonnegative parts of flag varieties and their topologies.

problem Understanding the topology of totally nonnegative flag varieties.
method Algebraic, geometric, and dynamical perspectives; orbit context; gradient flows; Riemannian metrics.
result Positivity is preserved in certain metrics on the totally nonnegative part of flag varieties.

Classifies finite orbits of mapping class group action on character varieties.

problem Classifying finite orbits of mapping class group action on character varieties of punctured spheres.
method Inductive proof using Lisovyy--Tykhyy's classification for 4-punctured spheres as base case.
result Proves no finite orbits for 7-punctured spheres and unique 1-parameter family for 6-punctured spheres.

The paper connects Legendrian links to cluster theory and exact Lagrangian fillings.

problem Understanding the relationship between Legendrian links and cluster theory.
method Using exact Lagrangian fillings and cluster theory, the paper establishes connections between Legendrian links and cluster varieties.
result The augmentation variety of certain Legendrian 2-bridge links is isomorphic to a product of cluster varieties.

In this paper we survey a number of recent results concerning the existence and moduli spaces of solutions of various geometric problems on noncompact manifolds. The three problems which we discuss in detail are: I. Complete properly immersed minimal surfaces in $\RR^3$ with finite total curvature. II. Complete embedde…

1996-01-18abs ↗pdf ↗

Study on braid monodromy of Lefschetz fibrations, proving infinite index subgroup.

problem Understanding the structure of braid monodromy in Lefschetz fibrations.
method Developed methods to show infinite index of subgroup, relating to character varieties.
result Proved infinite index subgroup for various cases of Lefschetz fibrations.

Machine learning predicts Kronecker coefficients with high accuracy.

problem Predicting Kronecker coefficients from tensor products of symmetric group representations.
method Training machine learning models (NN, CNN, GBDT) to classify Kronecker coefficients as zero or non-zero.
result Trained models achieve high accuracy (0.98\approx 0.98) in classifying Kronecker coefficients.

Abstract: Determines thermoelastic coefficients from boundary data.

problem Determining coefficients of thermoelastic system from boundary information.
method Explicit expression for thermoelastic Dirichlet-to-Neumann map with variable coefficients.
result Thermoelastic Dirichlet-to-Neumann map uniquely determines coefficients on the manifold.

New filling functions for groups with coefficients show different asymptotic behavior.

problem Difficulty in filling loops with surfaces in Cayley graphs.
method Defining homological filling functions with coefficients and proving their differences.
result Filling functions for nn-cycles with coefficients in different groups have distinct asymptotic behavior.

Abstract: Determines Lamé coefficients from boundary measurements.

problem Determining Lamé coefficients from elastic boundary measurements.
method Explicit symbol of elastic Dirichlet-to-Neumann map, partial derivatives determination.
result Elastic Dirichlet-to-Neumann map uniquely determines Lamé coefficients.

Efficiently optimizes constrained problems with two-step lookahead BO.

problem Optimizing constrained problems with limited computational resources.
method Two-step lookahead Bayesian optimization with inequality constraints, using a novel unbiased gradient estimator.
result Significantly improves query efficiency over previous methods.

Defines and proves properties of weighted renormalized volume coefficients.

problem None explicitly stated; focuses on mathematical definitions and proofs.
method Defines weighted renormalized volume coefficients and proves their variational nature and polynomial representation.
result Weighted renormalized volume coefficients are variational and can be expressed as polynomials of specific tensors.

Improved 3D LiDAR data classification using product coefficients.

problem Enhancing accuracy in 3D LiDAR data classification.
method Introducing product coefficients derived from measure theory as additional features in the classification process, alongside PCA.
result Significant improvement in classification accuracy with product coefficients.

We study the structure of the stable coefficients of the Jones polynomial of an alternating link. We start by identifying the first four stable coefficients with polynomial invariants of a (reduced) Tait graph of the link projection. This leads us to introduce a free polynomial algebra of invariants of graphs whose ele…

2013-09-23abs ↗pdf ↗

Paper calculates third coefficient in Kaehler-Einstein metric expansion.

problem Understanding Kaehler-Einstein metrics and their epsilon functions.
method Computes the third coefficient in the TYCZ-expansion of the epsilon function.
result Discovers the vanishing of the third coefficient's significance.

Develops local elliptic regularity for geometrically-natural operators with low regularity coefficients.

problem Local elliptic regularity for operators with low regularity coefficients in Sobolev-type spaces.
method Rescaling estimates and multiplication results for function spaces.
result Unified set of interior estimates and regularity inference for operators with Sobolev-type coefficients.

ePF improves PF for ITS by balancing exploration and exploitation, outperforming baselines.

problem Premature exploitation in PF leads to suboptimal solutions under constrained budgets.
method Integrates Entropic Annealing and Look-ahead Modulation to preserve diversity and evaluate potential.
result Significant improvement in task reward (up to 50% relative) on math benchmarks.

Extends A-type coefficient polynomials to B-type setting, introducing new invariants.

problem Tackles the B-type skein relation and introduces new coefficient polynomials.
method Introduces coefficient polynomials associated with the B-type skein relation and proves their invariance under Reidemeister moves.
result Shows that the generating series of these coefficient polynomials recovers the Kauffman polynomial.

We simplify complex regression coefficients using linearization and feature comparison.

problem Interpreting high-dimensional regression coefficients from nonlinear responses.
method Developed a linearization method to derive feature coefficients and compare them with regression coefficients.
result Shows how regression coefficients relate to linearized feature coefficients and how they change under regularization.

Bounding twist number of surface links using polynomial coefficients.

problem Bounding the twist number of alternating surface links.
method Introducing a generalized homological Kauffman bracket and applying it to surface link diagrams.
result A bound for the twist number of alternating surface links in terms of polynomial coefficients.

Characterizes differential forms and vector fields with constant coefficients on manifolds.

problem Understanding constant coefficient differential forms and vector fields on manifolds.
method Analyzes differential forms and vector fields of specific degrees, proving obstructions and characterizing solutions to partial differential systems.
result Characterizes differential forms and vector fields with constant coefficients of various degrees on smooth manifolds.

Study on gradient descent in Hilbert spaces with Markov chains, focusing on mixing coefficients.

problem Analyzing convergence of gradient descent in Hilbert spaces with stationary Markov chains.
method Examined strictly stationary Markov chains with φφ- and ββ-mixing coefficients, derived probabilistic upper bounds.
result Probabilistic upper bounds on convergence behavior of gradient descent algorithm based on mixing coefficients.

The conformal powers of the Laplacian of a Riemannian metric which are known as the GJMS-operators admit a combinatorial description in terms of the Taylor coefficients of a natural second-order one-parameter family (˝r;g)\H(r;g) of self-adjoint elliptic differential operators. (˝r;g)\H(r;g) is a non-Laplace-type perturbation …

2014-11-28abs ↗pdf ↗

Guts determine the leading coefficients of L2L^2-Alexander torsions for 3-manifolds.

problem Determining the leading coefficient of L2L^2-Alexander torsions for 3-manifolds.
method Using a new criterion for the convergence of Fuglede-Kadison determinants and the work of Agol and Zhang on guts of 3-manifolds.
result The leading coefficient equals the relative L2L^2-torsion of the guts associated to the cohomology class.

Diffusion models adapt to low-dimensional data regardless of coefficient choices.

problem Understanding how diffusion models adapt to low-dimensional data structures.
method Analysis of diffusion models with flexible coefficient choices.
result Proven that O~(k/ε)\widetilde{O}(k/\varepsilon) iterations suffice for accurate sampling in total variation distance.

GenMod uses generative models to approximate high-dimensional PDE solutions with limited evaluations.

problem Quantifying uncertainty in high-dimensional PDE systems with random parameters.
method Develops a method using generative models to approximate polynomial chaos coefficients in underdetermined systems.
result The method outperforms sparsity-promoting methods in approximating PDE solutions with limited evaluations.

Privacy amplification improved through contraction coefficients and EγE_γ-divergence.

problem Improving privacy guarantees in iterative algorithms.
method Using contraction coefficients derived from EγE_γ-divergence to determine differential privacy parameters.
result Tighter bounds on differential privacy parameters of iterative algorithms.