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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.

168,657 papers · 148 categories

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57114170227 · May 202619922001200920172026
48 results for normal crossings

Real analytic functions can be extended on manifolds with normal crossings.

problem Extending continuous functions to CωC^ω functions on manifolds with normal crossings.
method Employing Cartan Theorems A and B from real analytic geometry.
result Continuous functions on the union of submanifolds with normal crossings can be extended to CωC^ω functions on the entire manifold.

A well-known issue of Batch Normalization is its significantly reduced effectiveness in the case of small mini-batch sizes. When a mini-batch contains few examples, the statistics upon which the normalization is defined cannot be reliably estimated from it during a training iteration. To address this problem, we presen…

2020-02-13abs ↗pdf ↗

Pseudo links have two crossing types: classical crossings and indeterminate crossings. They were first introduced by Ryo Hanaki as a possible tool for analyzing images produced by electron microscopy of DNA. A normalized bracket polynomial is defined for pseudo links and then used to construct and obstruction to cosmet…

2015-12-15abs ↗pdf ↗

Harmonic unit normal sections studied for Grassmannians induced by cross products.

problem Energy of maps assigning unit vectors to subspaces of Grassmannians.
method Analyzing cross products to induce harmonic sections into sphere bundles.
result All unit normal sections of Grassmannians associated with cross products are harmonic.

We investigate a method of construction of Calabi--Yau manifolds, that is, by smoothing normal crossing varieties. We develop some theories for calculating the Picard groups of the Calabi--Yau manifolds obtained in this method. Some applications are included, such as construction of new examples of Calabi--Yau 3-folds …

2006-04-27abs ↗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.

In this paper we prove that the Kähler-Einstein metrics for a degeneration family of Kähler manifolds with ample canonical bundles Gromov-Hausdorff converge to the complete Kähler-Einstein metric on the smooth part of the central fiber when the central fiber has only normal crossing singularities inside smooth total sp…

2003-03-10abs ↗pdf ↗

This is the continuation of our paper \cite{GS}, to study the linear theory for equations with conical singularities. We derive interior Schauder estimates for linear elliptic and parabolic equations with a background Kähler metric of conical singularities along a divisor of simple normal crossings. As an application, …

2018-09-10abs ↗pdf ↗

Let XX be a non-singular compact Kähler manifold, endowed with an effective divisor D=(1βk)YkD= \sum (1-β_k) Y_k having simple normal crossing support, and satisfying βk(0,1)β_k \in (0,1). The natural objects one has to consider in order to explore the differential-geometric properties of the pair (X,D)(X, D) are the so-called metri…

2013-07-24abs ↗pdf ↗

This paper investigates the impact of normalization on deep neural networks for click-through rate prediction.

problem The effect of normalization on deep neural network models for CTR estimation.
method Systematic study of various normalization approaches applied to feature embedding and MLP part of DNN models.
result Correct normalization significantly enhances model performance, as demonstrated by extensive experiments on real-world datasets.

This paper improves bandwidth selectors for SPBNs to enhance their performance.

problem Suboptimal density estimation and reduced predictive performance in SPBNs due to normal rule bandwidth selection.
method Theoretical framework for state-of-the-art bandwidth selectors (cross-validation and plug-in methods) are established and evaluated.
result Cross-validation selectors outperform the normal rule, especially in high sample size scenarios.

We show that the first eigenvalue of a closed Riemannian surface normalized by the area can be strictly increased by attaching a cylinder or a cross cap. As a consequence we obtain the existence of maximizing metrics for the normalized first eigenvalue on any closed surface of fixed topological type. Since these metric…

2019-09-06abs ↗pdf ↗

Given a 2-crossing minimal chart ΓΓ, a minimal chart with two crossings, set α=min{ i  α=\min\{~i~|~there exists an edge of label ii containing a white vertex}\}, and β=max{ i  β=\max\{~i~|~there exists an edge of label ii containing a white vertex}\}. In this paper we study the structure of a neighbourhood of ΓαΓβΓ_α\cupΓ_β, and p…

2017-09-26abs ↗pdf ↗

We show that there exists a suitable neighborhood of a constant curvature hyperbolic metric such that, for all initial data in this neighborhood, the corresponding solution to a normalized cross curvature flow exists for all time and converges to a hyperbolic metric. We show that the same technique proves an analogous …

2006-09-27abs ↗pdf ↗

We study fundamental groups of projective varieties with normal crossing singularities and of germs of complex singularities. We prove that for every finitely-presented group G there is a complex projective surface S with simple normal crossing singularities only, so that the fundamental group of S is isomorphic to G. …

2011-09-19abs ↗pdf ↗

Improved estimators for causal inference using cross-fitting and undersmoothing.

problem Estimating expected conditional covariance in causal inference.
method Double cross-fit doubly robust (DCDR) estimators with undersmoothing for non-smooth nuisance functions.
result DCDR estimators achieve n\sqrt{n}-consistency and asymptotic normality under minimal conditions.

New structures allow for self-crossing singularities, leading to new families of stable generalized complex manifolds.

problem Stable generalized complex structures in higher dimensions with self-crossing singularities.
method Extending stable generalized complex structures to include anticanonical sections with normal self-crossings.
result Construction of large families of stable generalized complex manifolds in four dimensions.

This paper classifies ball quotients of the complex projective plane.

problem Understanding the structure of the complex projective plane as a ball quotient.
method Analyzing the branch locus as a line arrangement and smooth normal-crossing curves.
result The orbifold structure of (P2,D)(\mathbb{P}^2,D) is isomorphic to either the Deligne-Mostow example or a certain degree 9 cover.

The paper strengthens a theorem on crossings under linear perturbations with Hausdorff measure estimates.

problem Understanding multiple-point crossings under linear perturbations.
method Establishes a transversality theorem with Hausdorff measure estimates for exceptional parameter sets.
result Explicit upper bounds on the Hausdorff dimension of the exceptional set.

New model identifies microbial subcommunities robustly, accounting for cross-sample heterogeneity.

problem Inference in LDA is sensitive to the number of subcommunities and often creates artificial ones.
method Incorporates logistic-tree normal (LTN) model into LDA to account for cross-sample heterogeneity.
result Restores robustness of inference and identifies meaningful subcommunities.

A new method speeds up SoftMax normalization for embedding learning.

problem Efficiently learning distributed representations with SoftMax normalization.
method Proposes a linear-time heuristic approximation for mSoftMax(XYT){ m SoftMax}(XY^T), optimizing cross entropy.
result Achieves higher or comparable accuracy to existing methods with lower computational time.

The paper analyzes the risk of CV-tuned regularized estimators and connects it to SURE.

problem Understanding the risk of CV-tuned regularized estimators.
method Derives asymptotic risk function of CV-tuned estimators and connects it to SURE.
result The risk function provides a more detailed picture of predictive performance than uniform bounds.

We establish a new extension result for twisted canonical forms defined on a hypersurface with simple normal crossings of a projective manifold. Some of the examples presented in the appendix are showing that the bounds we obtain for the extension are sharp.

2020-02-12abs ↗pdf ↗

We study sharp asymptotics of the first eigenvalue on Riemannian surfaces obtained from a fixed Riemannian surface by attaching a collapsing flat handle or cross cap to it. Through a careful choice of parameters this construction can be used to strictly increase the first eigenvalue normalized by area if the initial su…

2019-09-06abs ↗pdf ↗

A new type of knot energy is presented via real life experiments involving a thin resilient metallic tube. Knotted in different ways, the device mechanically acquires a uniquely determined (up to isometry) normal form at least when the original knot diagram has a small number of crossings, thus outperforming the famous…

2010-11-22abs ↗pdf ↗

Researchers prove existence of metrics maximizing Laplace eigenvalue on all closed surfaces.

problem Proving the existence of metrics maximizing the first Laplace eigenvalue on closed surfaces.
method By contradiction and refinement of techniques, proving strict monotonicity under surface modifications.
result Existence of metrics maximizing the area-normalized first eigenvalue on all closed surfaces.

We prove a global residual formula in terms of logarithmic indices for one-dimensional holomorphic foliations, with isolated singularities, and logarithmic along normal crossing divisors. We also give a formula for the total sum of the logarithmic indices if the singular set of the foliation is contained in the invaria…

2018-09-19abs ↗pdf ↗

Enhances multimodal generation with Normalizing Flows and correlation analysis.

problem Generating coherent cross-modal data from multiple sources.
method Uses Deep Canonical Correlation Analysis for shared information, Normalizing Flows for diversity, and Product of Experts for scalability.
result Improves likelihood, diversity, and coherence in conditional generation.

Proposes a method to solve deep neural networks' local minimum problem.

problem Local minimum problem in deep neural networks training.
method Transforms cross-entropy loss into risk-averse error criterion, adjusts RSI, and uses convexity region.
result Trained deep learning machine is expected to be inside a global minimum's attraction basin.

We prove that the first Chern form of the moduli space of polarized Calabi-Yau manifolds, with the Hodge metric or the Weil-Petersson metric, represent the first Chern class of the canonical extensions of the tangent bundle to the compactification of the moduli space with normal crossing divisors.

2014-12-23abs ↗pdf ↗