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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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18355370 · May 202619922001200920172026
48 results for hyperbolic 2-ball

We study the space C(a0,a1,,an)C(a_0,a_1,\dots,a_n) of hyperbolic 2-spheres with cone points of prescribed apex curvatures 2a0,2a1,,2an]0,2π[2a_0,2a_1,\dots,2a_n\in]0,2π[ and some related spaces. For n=3n=3, we get a detailed description of such spaces. The euclidean 2-spheres were considered by W. P. Thurston: for n=4n=4, the corresponding space…

2018-01-01abs ↗pdf ↗

We establish sharp Sobolev inequalities of order four on Euclidean d-balls for d greater than or equal to four. When d=4, our inequality generalizes the classical second order Lebedev-Milin inequality on Euclidean 2-balls. Our method relies on the use of scattering theory on hyperbolic d-balls. As an application, we ch…

2015-09-20abs ↗pdf ↗

An ideal triangulation T\mathcal{T} of a hyperbolic 3-manifold MM with one cusp is non-peripheral if no edge of T\mathcal{T} is homotopic to a curve in the boundary torus of MM. For such a triangulation, the gluing and completeness equations can be solved to recover the hyperbolic structure of MM. A planar project…

2016-10-31abs ↗pdf ↗

We describe and study the loci equidistant from finitely many points in the so-called complex hyperbolic geometry, i.e., in the geometry of a holomorphic 22-ball B\Bbb B. In particular, we show that the bisectors (= the loci equidistant from 22 points) containing the (smooth real algebraic) curve equidistant from gi…

2014-06-23abs ↗pdf ↗

In this paper we review the development and recent results of the Siu-Yang conjecture which is that every Kähler-Einstein compact complex manifold of complex dimension two with negative sectional curvature is biholomorphic to a compact quotient of the complex 2-ball.

2019-06-24abs ↗pdf ↗

K-means clustering improved for robustness to outliers and distribution shifts.

problem K-means is brittle to outliers, distribution shifts, and limited samples.
method Developed a distributionally robust variant using Wasserstein-2 ball around the empirical distribution.
result Substantial gains in outlier detection and robustness to noise demonstrated.

This paper contains a construction of a finite set X in the boundary of the unit 3-ball in R^3 whose minimal tree is knotted. The example answers Problem 5.17 in ''Problems in Low-dimensional Topology'' by Rob Kirby posed by Michael Freedman: ''Given a finite set of points X in the boundary of B^3, let T be a tree in B…

1998-06-15abs ↗pdf ↗

Fusion of robustness and uncertainty techniques improves adversarial defense.

problem Adversarial attacks on deep neural networks.
method Integrating uncertainty quantification into randomized smoothing for robustness guarantees.
result Improved robustness guarantees for uncertainty aware classifiers.

We prove an equidistribution result for totally geodesic submanifolds in a compact locally symmetric space. In the case of Hermitian locally symmetric spaces, this gives a convergence theorem for currents of integration along totally geodesic subvarieties. As a corollary, we obtain that on a complex surface which is a …

2014-07-24abs ↗pdf ↗

New algorithm reduces online logistic regression regret without exponential constant.

problem Improper learning in online logistic regression with logarithmic regret.
method Regularized empirical risk minimization with surrogate losses.
result Regret scaling as O(B log(Bn)) with low computational complexity.

Local robustness ensures that a model classifies all inputs within an 2\ell_2-ball consistently, which precludes various forms of adversarial inputs. In this paper, we present a fast procedure for checking local robustness in feed-forward neural networks with piecewise-linear activation functions. Such networks partit…

2020-02-12abs ↗pdf ↗

We consider a stochastic continuum armed bandit problem where the arms are indexed by the 2\ell_2 ball Bd(1+ν)B_{d}(1+ν) of radius 1+ν1+ν in Rd\mathbb{R}^d. The reward functions r:Bd(1+ν)Rr :B_{d}(1+ν) \rightarrow \mathbb{R} are considered to intrinsically depend on kdk \ll d unknown linear parameters so that $r(\mathbf{x}) = g(\ma…

2013-12-01abs ↗pdf ↗

Paper studies robust MDPs, improving sample complexity and asymptotic performance.

problem Optimal robust policy and value function in robust MDPs with generative models.
method Improves prior results on non-asymptotic and asymptotic performances of robust MDPs, considering various uncertainty sets.
result Improved sample complexity and asymptotic normality of optimal robust value function.

As application demands for online convex optimization accelerate, the need for designing new methods that simultaneously cover a large class of convex functions and impose the lowest possible regret is highly rising. Known online optimization methods usually perform well only in specific settings, and their performance…

2019-06-01abs ↗pdf ↗

Estimating signals with linear recurrence relations under Gaussian noise is nearly as hard as sparse signals.

problem Estimating discrete-time signals with unknown linear recurrence relations in Gaussian noise.
method Analyzing shift-invariant subspaces and their Fourier coefficients as reproducing filters.
result The statistical complexity is nearly the same as for ss-sparse signals, and the estimator is tractable.

Recursive training of generative models can lead to model collapse, and the recursion converges to a unique limiting distribution.

problem Model collapse in recursive training of generative models
method Recursive training on their own outputs
result Recursive training converges to a unique limiting distribution

Paper proves convergence for private FL on non-Lipschitz convex objectives using normalization instead of clipping.

problem Lack of convergence results for differentially private federated learning with non-Lipschitz objectives.
method Developed a convergence result for private FL on smooth convex objectives without assuming Lipschitzness, using normalization instead of clipping.
result Normalization-based private FL algorithm converges better than clipping-based counterpart on smooth convex functions.

Unified framework for uniform signal recovery in nonlinear GCS with 1-bit/quantized measurements.

problem Uniform recovery guarantees for nonlinear generative compressed sensing.
method Unified framework using generalized Lasso and Lipschitz approximation.
result Uniform recovery of all signals in the ball up to an error of ε using approximately O(k/ε^2) samples.

The paper defines two types of hyperbolicity for complex manifolds and proves related results.

problem Defining and studying hyperbolicity for a broader class of complex manifolds.
method Introducing SKT hyperbolicity and Gauduchon hyperbolicity, proving results using SKT and Gauduchon metrics.
result Every SKT hyperbolic manifold is also Kobayashi/Brody hyperbolic and every Gauduchon hyperbolic manifold is divisorially hyperbolic.

Introduces hyperbolic generalized framed surfaces and their properties.

problem None explicitly stated; focuses on introducing new geometric objects.
method Generalization of hyperbolic framed surfaces and curves.
result Established conditions for a surface to be a hyperbolic generalized framed base surface and explored their singularities.

Study on new hyperbolicity notions for non-Kähler manifolds and their deformations.

problem Analyzing new hyperbolicity notions for non-Kähler complex manifolds.
method Introducing and analyzing two new notions of hyperbolicity for compact complex non-Kähler manifolds, and studying their behavior under smooth modifications.
result Established openness results for pp-HS hyperbolicity and pp-Kähler hyperbolicity under holomorphic deformations.

Study complex hyperbolic lattices and their relation to strict hyperbolization.

problem Understanding the relationship between complex hyperbolic lattices and strict hyperbolization.
method Analyzing the fundamental groups of complex hyperbolic manifolds and spaces arising from strict hyperbolization.
result Uniform lattices in PU(n,1) cannot be fundamental groups of Charney-Davis strict hyperbolizations when n ≥ 2.

Paper finds inequalities for convex domains in hyperbolic space.

problem Finding inequalities for convex domains in hyperbolic space.
method Introducing hyperbolic ellipsoids and using orthogonal projection to establish inequalities.
result Affine isoperimetric inequalities for static convex domains in hyperbolic space characterized by hyperbolic ellipsoids.

We show that a relatively hyperbolic graph with uniformly hyperbolic peripheral subgraphs is hyperbolic. As an application, we show that the disc graph and the electrified disc graph of a handlebody H of genus g>1 are hyperbolic, and we determine their Gromov boundaries.

2014-03-04abs ↗pdf ↗

HKConv learns hyperbolic features by aggregating kernel points.

problem Challenges in learning good hyperbolic representations using Euclidean operations.
method Proposes HKConv, a trainable hyperbolic convolution that correlates local features with kernel points and aggregates them.
result HKConv learns expressive local features according to hyperbolic geometry and enjoys equivariance to permutation and invariance to parallel transport.

We show the equivalence of several characterizations of relative hyperbolicity for metric spaces, and obtain extra information about geodesics in a relatively hyperbolic space. We apply this to characterize hyperbolically embedded subgroups in terms of nice actions on (relatively) hyperbolic spaces. We also study the d…

2012-10-30abs ↗pdf ↗