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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.

168,695 papers · 148 categories

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275380106 · May 202619922001200920172026
48 results for interval bundles

We show that if L\mathcal{L} is a codimension-one lamination in a finite volume hyperbolic 3-manifold such that the principal curvatures of each leaf of L\mathcal{L} are all in the interval (δ,δ)(-δ,δ) for a fixed δ[0,1)δ\in[0,1) and no complimentary region of L\mathcal{L} is an interval bundle over a surface, then each bo…

2009-01-09abs ↗pdf ↗

Let G be compact Lie group. It is shown that the cotangent bundle of the complexification of G admits a hyperkahler structure which is invariant under left and right translations by elements of G. The proof is to realize the cotangent bundle of the complex group as a moduli space of solutions to Nahm's equations on the…

2004-09-15abs ↗pdf ↗

We consider cohomogeneity one homogeneous disk bundles and adress the question when these admit a nonnegatively curved invariant metric with normal collar, i.e., such that near the boundary the metric is the product of an interval and a normal homogeneous space. If such a bundle is not (the quotient of) a trivial bundl…

2008-06-24abs ↗pdf ↗

Kapustin and Witten associate a Hecke modification of a holomorphic bundle over a Riemann surface to a singular monopole on a Riemannian surface times an interval satisfying prescribed boundary conditions. We prove existence and uniqueness of singular monopoles satisfying prescribed boundary conditions for any given He…

2008-04-23abs ↗pdf ↗

In this thesis, we employ simplicial methods to study actions, principal bundles, and bibundles of higher groupoids. Roughly, we use Kan fibrations to model actions of higher groupoids, we use pairs of a Kan fibration and a special acyclic fibration to model principal bundles of higher groupoids, we use inner Kan fibra…

2015-12-14abs ↗pdf ↗

Let M be a twisted interval bundle over a nonorientable hyperbolizable surface. Let X(M) be the PSL(2,C)-character variety of π_1(M). We examine the dynamics of the action of Out(π_1(M)) on X(M), and in particular, we find an open set on which the action is properly discontinuous that is strictly larger than the interi…

2011-03-17abs ↗pdf ↗

Study of flows on circle bundles over translation surfaces, showing decay of correlations.

problem Ergodic properties of flows on circle bundles over translation surfaces.
method Generalizing Heisenberg nilflows to more general base surfaces, showing relatively mixing.
result Showed that such flows exhibit decay of correlations in the orthogonal complement of functions constant along fibers.

We take a first step towards understanding the relationship between foliations and universally tight contact structures on hyperbolic 3-manifolds. If a surface bundle over a circle has pseudo-Anosov holonomy, we obtain a classification of "extremal" tight contact structures. Specifically, there is exactly one contact s…

2001-10-10abs ↗pdf ↗

We give time-slicing path integral formulas for solutions to the heat equation corresponding to a self-adjoint Laplace type operator acting on sections of a vector bundle over a compact Riemannian manifold with boundary. More specifically, we show that such a solution can be approximated by integrals over finite-dimens…

2016-07-18abs ↗pdf ↗

We establish a criterion for certain mapping classes of a surface homeomorphisms to be pseudo-Anosov in terms of the geometry of hyperbolic 3-manifolds and Gromov-hyperbolic surface group extensions. Specifically, any element of the fundamental group of a surface S gives rise to a mapping class on the punctured surface…

2012-08-13abs ↗pdf ↗

In this note we show that for the group G = U(N) the space of Hecke modifications of a rank N vector bundle over a Riemann surface C coincides with the moduli space of solutions of certain non-abelian vortex equations over C . Through the recent work of Kapustin and Witten this then leads to an isomorphism between the …

2009-07-10abs ↗pdf ↗

Having a regression model, we are interested in finding two-sided intervals that are guaranteed to contain at least a desired proportion of the conditional distribution of the response variable given a specific combination of predictors. We name such intervals predictive intervals. This work presents a new method to fi…

2014-02-24abs ↗pdf ↗

Study the Bochner-Schrödinger operator on symplectic manifolds, proving gap existence and asymptotic kernel behavior.

problem Analyzing the spectrum and asymptotic behavior of the Bochner-Schrödinger operator on symplectic manifolds.
method Rough asymptotic description, existence proof, off-diagonal exponential estimate, complete asymptotic expansion.
result Existence of gaps in the spectrum and asymptotic kernel behavior.

Study of solitons in Laplacian flow on 7-manifolds.

problem Understanding finite-time singularities of Laplacian flow on G_2-structures.
method Systematic study of cohomogeneity-one solitons with Sp(2) and SU(3) symmetry groups.
result Existence and classification of smoothly-closing solitons, including complete and incomplete solutions.

Prediction intervals are a valuable way of quantifying uncertainty in regression problems. Good prediction intervals should be both correct, containing the actual value between the lower and upper bound at least a target percentage of the time; and tight, having a small mean width of the bounds. Many prior techniques f…

2018-06-28abs ↗pdf ↗

New methods for ordinal classification of interval-valued data and functional data.

problem Ordinal classification of interval-valued data and functional data.
method Six ordinal classifiers are proposed, including parametric, binary decomposition, logistic regression, distance-based, k-nearest-neighbor, kernel PCA, and random forest methods.
result Considering ordering and interval-valued information improves the accuracy of ordinal classification.

Proposes a method to create prediction intervals for neural networks using cross-validation.

problem Lack of prediction intervals for neural networks.
method k-fold cross-validation to construct conformal prediction intervals.
result Proposed method produces narrower intervals with similar coverage compared to SC method.

The statistical properties of the return intervals τqτ_q between successive 1-min volatilities of 30 liquid Chinese stocks exceeding a certain threshold qq are carefully studied. The Kolmogorov-Smirnov (KS) test shows that 12 stocks exhibit scaling behaviors in the distributions of τqτ_q for different thresholds qq. …

2008-07-11abs ↗pdf ↗

CONTINA provides adaptive confidence intervals for traffic demand prediction.

problem Uncertainty in future traffic demand predictions and the need for valid confidence intervals.
method Adaptive confidence interval method that adjusts based on deployment errors.
result Valid confidence intervals with shorter lengths and theoretical coverage guarantee.

The paper presents a method for generating well-calibrated prediction intervals using quality-driven deep ensembles.

problem Generating reliable prediction intervals for regression analysis.
method A multi-objective loss function combining quality measures for prediction intervals and point estimates, with a penalty function to ensure semantic integrity and stability.
result The method produces well-calibrated prediction intervals and point estimates, capturing both aleatoric and epistemic uncertainty.

Analyzes biased random walks and corrupted intervals in adversarial settings.

problem Learning thresholds and intervals in adversarial conditions.
method Analyzes biased random walks and corrupted intervals under adversarial design.
result Analyzes the expected behavior of biased random walks and corrupted intervals.

Paper introduces a new method for classifying interval-valued time series.

problem Classification of interval-valued time series.
method Extends point-valued time series imaging methods to interval-valued scenarios using DKD_K-distance and employs deep learning for classification.
result Proposed method achieves superior classification performance compared to existing methods.

Extends Fisher's Discriminant Analysis for interval-valued data.

problem Classifying entities represented by intervals and histograms.
method Adapts Fisher's Discriminant Analysis using Moore's interval arithmetic and Mallows' distance.
result Discriminant directions for interval-valued data are numerically maximized.

Study optimality conditions for interval-valued optimization problems on Riemannian manifolds.

problem Optimizing interval-valued functions on Riemannian manifolds under a total order relation.
method Generalized Hukuhara directional differentiability to derive KKT-type optimality conditions.
result Derives optimality conditions for interval-valued optimization problems on Riemannian manifolds.

This work challenges the assumption that shorter conformal prediction intervals are always better.

problem The conventional evaluation of conformal prediction metrics (coverage and interval length) may not fully capture the quality of predictions.
method The Prejudicial Trick (PT) is introduced, which probabilistically returns either a null interval or a longer one to maintain valid coverage while potentially reducing interval length.
result The Prejudicial Trick can yield deceptively shorter intervals without compromising coverage, but introduces practical vulnerabilities.

We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold qq for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the …

2007-09-11abs ↗pdf ↗

Extending methods first used by Casson, we show how to verify a hyperbolic structure on a finite triangulation of a closed 3-manifold using interval arithmetic methods. A key ingredient is a new theoretical result (akin to a theorem by Neumann-Zagier and Moser for ideal triangulations upon which HIKMOT is based) showin…

2019-04-27abs ↗pdf ↗

New confidence intervals improve treatment effect estimation in randomized experiments.

problem Improving confidence intervals for treatment effects in randomized experiments.
method Systematic exploitation of negative dependence or variance adaptivity.
result Achieved nonasymptotic confidence intervals with the same effective sample size as asymptotic ones.

Practical or scientific considerations often lead to selecting a subset of parameters as ``important.'' Inferences about those parameters often are based on the same data used to select them in the first place. That can make the reported uncertainties deceptively optimistic: confidence intervals that ignore selection g…

2019-06-02abs ↗pdf ↗

Random Forests provide interpretable prediction intervals with theoretical guarantees.

problem Lack of uncertainty estimates in machine learning point predictions.
method Out-of-Bag procedure for generating parametric and non-parametric prediction intervals.
result Proposed prediction intervals deliver correct coverage rates and narrow lengths.

BCI provides calibrated prediction intervals for time series forecasts.

problem Calibration of prediction intervals for time series forecasts.
method BCI wraps around any time series forecasting models and optimizes interval lengths using dynamic programming.
result BCI achieves long-term coverage under arbitrary distribution shifts and temporal dependence.