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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.

168,742 papers · 148 categories

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48 results for smoothed moment indicators

Develops a novel fast bootstrap for dependent data with higher-order accuracy.

problem Estimation of parametric and semi-parametric models for dependent data.
method i.i.d. resampling of smoothed moment indicators, asymptotic refinements under mild assumptions.
result Higher-order correct asymptotic confidence distributions and confidence intervals.

Real moment-angle manifolds of combinatorially equivalent simple polytopes are equivariantly diffeomorphic.

problem Uniqueness of smooth structures on real moment-angle manifolds.
method Arguments from calculus applied to results from complex moment-angle manifolds.
result Real moment-angle manifolds of combinatorially equivalent simple polytopes are equivariantly diffeomorphic.

A new method for generating samples without training, using smoothed score matching.

problem Generating samples efficiently and without training.
method Moment-matched score-smoothed overdamped Langevin dynamics (MM-SOLD).
result The method enables fast, robust, training-free sampling with competitive sample fidelity and diversity.

Paper proposes a new Taylor moment expansion for non-linear Gaussian filtering and smoothing.

problem Non-linear Gaussian filtering and smoothing in continuous-discrete state-space models.
method Taylor moment expansion (TME) for moment functions directly and in time variable.
result Significantly outperforms state-of-the-art methods in terms of estimation accuracy and numerical stability.

We define a moment map associated to a smooth torus action on a smooth manifold, without a two-form. We define cobordisms of such structures, allowing non compact manifolds as long as the moment maps are proper. We prove that a compact manifold with a torus action and a moment map is cobordant to the disjoint union of …

1997-01-19abs ↗pdf ↗

Kähler-Einstein metrics found on special types of symmetric varieties.

problem Finding Kähler-Einstein metrics on smooth Fano symmetric varieties with specific properties.
method Used a combinatorial criterion for K-stability of Fano spherical varieties and computed algebraic moment polytopes and barycenters.
result Proved all smooth Fano symmetric varieties with Picard number one admit Kähler-Einstein metrics.

New SGMM algorithm for efficient estimation of moment restriction models.

problem Estimation and inference on overidentified moment restriction models.
method Stochastic Approximation to Generalized Method of Moments (SGMM).
result SGMM offers fast and scalable implementation with streaming dataset handling.

The paper trivializes moment maps for various geometric structures.

problem Trivializing moment maps for different geometric structures.
method General framework of a reductive group GG acting on a smooth affine variety, using Kempf-Ness theory, Morse theory, and ideas from Nakajima and Kronheimer.
result Locally trivial fibration of moment maps over a regular locus of the center of the Lie algebra of a maximal compact subgroup.

New method for adaptive estimation and inference in econometric models without knowing smoothness.

problem Adaptive estimation and inference in ill-posed linear inverse problems with unknown smoothness.
method Discrepancy principle-based framework for adaptive hyperparameter selection.
result Achieves optimal rates in weak and strong metrics for linear functionals.

Study on rational projective planes with small index singularities.

problem Existence and classification of rational homology projective planes with small index quotient singularities.
method Topological and smooth obstructions analysis, classification of singularities.
result Classification of quotient singularities for rational homology projective planes with indices up to three.

MOMENT selects and estimates mixed-effects models using moment identities.

problem Selecting and estimating random-effects covariance matrix and fixed-effects coefficients in multiresponse linear mixed-effects models.
method MOMENT is a stage-wise moment-based framework that reduces the random-effects selection problem to a smooth constrained convex optimization problem.
result MOMENT performs competitively and can outperform separate univariate analyses for correlated responses.

Graph spectra have been successfully used to classify network types, compute the similarity between graphs, and determine the number of communities in a network. For large graphs, where an eigen-decomposition is infeasible, iterative moment matched approximations to the spectra and kernel smoothing are typically used. …

2018-04-18abs ↗pdf ↗

New method approximates diffusion process posteriors using moment functions.

problem Approximating posteriors of stochastic differential equations.
method Constructs variational process as controlled prior, approximates posterior with moment functions, uses natural gradient descent.
result Richer variational approximations for state-dependent diffusion terms.

Paper provides Edgeworth expansions for network moments, improving accuracy of sampling distributions.

problem Accurate descriptions of sampling distributions of network moment statistics.
method Edgeworth expansion applied to studentized network moment statistics.
result Higher-order accurate approximation to sampling CDF of network moment statistics.

Post-estimation smoothing improves prediction accuracy with structural indices.

problem Using natural structural indices in machine learning without losing robustness.
method A post-estimation smoothing operator that separates from the original predictor.
result Post-estimation smoothing improves accuracy over original predictors under simple conditions.

Let G be a complex reductive group and K a maximal compact subgroup. If X is a smooth projective G-variety, with a fixed (not necessarily integral) K-invariant Kaehler form, then the K-action is Hamiltonian. Let M be the zero fiber of the corresponding moment map. It is well known that the quotient M/K is a complex spa…

1997-12-19abs ↗pdf ↗

The paper proves that Gaussian field critical points have finite moments.

problem Proving the finiteness of moments for Gaussian field critical points.
method General approach not specific to critical points, using Taylor polynomial non-degeneracy.
result The finiteness of moments of the number of critical points of Gaussian fields.

In this paper we shall illustrate that each polytopal moment-angle complex can be understood as the intersection of the minima of corresponding Siegel leaves and the unit sphere, with respect to the maximum norm. Consequently, an alternative proof of a rigidity theorem of Bosio and Meersseman is obtained; as piecewise …

2014-04-06abs ↗pdf ↗

New real algebraic maps with prescribed images and compositions are constructed locally like moment maps.

problem Constructing real algebraic maps with specific properties and compositions.
method Explicit construction of real algebraic hypersurfaces and maps with prescribed images and compositions.
result Explicit families of functions represented as compositions of constructed maps with canonical projections.

We propose moment-based variational inference as a flexible framework for approximate smoothing of latent Markov jump processes. The main ingredient of our approach is to partition the set of all transitions of the latent process into classes. This allows to express the Kullback-Leibler divergence between the approxima…

2019-05-14abs ↗pdf ↗

Study nearly parallel G2-structures with torus symmetry using multi-moment maps.

problem Characterize and construct nearly parallel G2-structures with torus symmetry.
method Use multi-moment map techniques and analyze the geometry of the base spaces.
result Locally, the construction may produce examples with four-torus symmetry.

The author studies regions foliated by 1D families of functions and their applications.

problem Understanding regions represented as foliated forms and natural smooth maps onto them.
method Investigates natural smooth maps respecting canonical projections and moment maps, focusing on foliated regions.
result Discusses the 1st derivative of functions and critical sets in foliated regions.

We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of computing/approximating the means and covariances of joint probabilities. This implies that novel filters and …

2010-06-10abs ↗pdf ↗

Paper explores ML for UV spectra, showing transferability in chemical space.

problem Modeling excited states and predicting properties of unseen molecules.
method Adapting charge model for excited states, using SchNarc approach.
result ML models can predict properties of unseen molecules and different excited states.

Study the geometry of twistor spaces with rotating circle action.

problem Holomorphic symplectic geometry of twistor spaces.
method Interpreting Hitchin's meromorphic connection and studying critical points of moment maps.
result Residue of Hitchin's meromorphic connection serves as a moment map for the circle action.

New SQ lower bound shows complexity nearly matches known upper bound for smoothed agnostic learning.

problem Smoothed agnostic learning of halfspaces under subgaussian distributions.
method Statistical Query (SQ) lower bound using moment-matching hard distribution and linear programming duality.
result First non-trivial lower bound on complexity nearly matches known upper bound.

We present a novel framework for kernel learning with sequential data of any kind, such as time series, sequences of graphs, or strings. Our approach is based on signature features which can be seen as an ordered variant of sample (cross-)moments; it allows to obtain a "sequentialized" version of any static kernel. The…

2016-01-29abs ↗pdf ↗