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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.

168,695 papers · 148 categories

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1122 · Oct 202519922001200920172026
8 results for Qn+1

The paper defines Vn-slant helices in a lightlike cone and their curvature functions.

problem Understanding Vn-slant helices in a lightlike cone Qn+1.
method Defined Vn-slant helices and their harmonic curvature functions in Qn+1, expressed differential equations, and provided conditions for being Vn-slant helices.
result Differential equations of harmonic curvature functions and necessary conditions for Vn-slant helices in Qn+1.

Let ρρ be a maximal representation of a uniform lattice ΓSU(n,1)Γ\subset{\rm SU}(n,1), n2n\geq 2, in a classical Lie group of Hermitian type HH. We prove that necessarily H=SU(p,q)H={\rm SU}(p,q) with pqnp\geq qn and there exists a holomorphic or antiholomorphic ρρ-equivariant map from complex hyperbolic space to the symmetric sp…

2015-06-24abs ↗pdf ↗

In this paper, we study the hyperbolicity of arborescent tangles and arborescent links. We will explicitly determine all essential surfaces in arborescent tangle complements with non-negative Euler characteristic, and show that given an arborescent tangle T, the complement X(T) is non-hyperbolic if and only if T is a r…

2008-01-30abs ↗pdf ↗

In many learning tasks, structural models usually lead to better interpretability and higher generalization performance. In recent years, however, the simple structural models such as lasso are frequently proved to be insufficient. Accordingly, there has been a lot of work on "superposition-structured" models where mul…

2015-09-08abs ↗pdf ↗

A scalable PyTorch framework for non-crossing quantile regression.

problem Non-crossing quantile regression to avoid impossible negative probability densities.
method CJQR-ALM combining Augmented Lagrangian Method, differentiable pinball loss, and L-BFGS optimization.
result Achieves near-zero crossing rates on large datasets within minutes.

New algorithm detects communities near KS threshold with optimal rate, even in noisy conditions.

problem Community detection in symmetric stochastic block models with noisy data.
method Polynomial-time algorithm using Sum-of-Squares framework and robust majority voting.
result Achieves minimax-optimal misclassification rate near Kesten-Stigum threshold, even with node corruption.