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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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54108161215 · May 202619922001200920172026
48 results for higher-order smoothness

We provide improved convergence rates for various \emph{non-smooth} optimization problems via higher-order accelerated methods. In the case of \ell_\infty regression, we achieves an O(ε4/5)O(ε^{-4/5}) iteration complexity, breaking the O(ε1)O(ε^{-1}) barrier so far present for previous methods. We arrive at a similar rate fo…

2019-06-04abs ↗pdf ↗

Unified approach to discrete and smooth isoperimetric inequalities of arbitrary order.

problem Finding higher order isoperimetric inequalities for both discrete and smooth curves.
method Unified approach via Fourier analysis of linear operators.
result Unified upper and lower bounds for isoperimetric deficit in smooth curves.

Lower bounds for higher-order methods in non-convex optimization.

problem Proving lower bounds for higher-order methods in smooth non-convex finite-sum optimization.
method Analyzing deterministic and randomized algorithms, proposing a new smoothness assumption.
result Proves optimal lower bounds for simulating pth-order regularized methods on the whole function.

State-of-the-art methods in convex and non-convex optimization employ higher-order derivative information, either implicitly or explicitly. We explore the limitations of higher-order optimization and prove that even for convex optimization, a polynomial dependence on the approximation guarantee and higher-order smoothn…

2017-10-27abs ↗pdf ↗

Study optimizes zero-order strongly convex function minimization with higher order smoothness.

problem Optimizing a strongly convex function with noisy evaluations.
method Randomized approximation of projected gradient descent with smoothing kernel.
result Upper bounds and minimax lower bounds for the algorithm, showing near-optimality.

We deduce from the work of Chen, that the restriction morphism from closed free iterated integrals to closed iterated integrals on loops is onto. We use this to show that the module of higher order invariants of smooth functions is generated by free closed iterated integrals.

2010-11-15abs ↗pdf ↗

The present paper is a follow up of our paper \cite{nS}. We investigate here the maximization of higher order eigenvalues in a conformal class on a smooth compact boundaryless Riemannian surface. Contrary to the case of the first nontrivial eigenvalue as shown in \cite{nS}, bubbling phenomena appear.

2015-04-28abs ↗pdf ↗

Introduce Collapsed Effective Operators for higher-order structures.

problem Existing spectral operators decompose topology into separate ranks, leaving practitioners to fuse information back to vertices.
method Introduce Collapsed Effective Operators via Schur complementation of a graded Laplacian.
result Preserves positive semi-definiteness, lowers system energy under higher-order connectivity.

We develop and implement a novel fast bootstrap for dependent data. Our scheme is based on the i.i.d. resampling of the smoothed moment indicators. We characterize the class of parametric and semi-parametric estimation problems for which the method is valid. We show the asymptotic refinements of the proposed procedure,…

2020-01-14abs ↗pdf ↗

Mean curvature flow of clusters of n-dimensional surfaces in R^{n+k} that meet in triples at equal angles along smooth edges and higher order junctions on lower dimensional faces is a natural extension of classical mean curvature flow. We call such a flow a mean curvature flow with triple edges. We show that if a smoot…

2016-05-21abs ↗pdf ↗

The present paper develops two concepts of pointwise differentiability of higher order for arbitrary subsets of Euclidean space defined by comparing their distance functions to those of smooth submanifolds. Results include that differentials are Borel functions, higher order rectifiability of the set of differentiabili…

2016-03-28abs ↗pdf ↗

Improves safety region certification for smoothed classifiers without changing smoothing scheme.

problem Certified safety regions for smoothed classifiers are often small compared to optimal.
method Generalizes certified radius calculation as nested optimization problem, uses 0th-1st order information, and designs efficient estimators.
result Certified safety regions are significantly larger than current methods, achieving significant improvements on various metrics.

Paper improves stochastic bilevel optimization methods for highly-smooth problems.

problem Finding εε-stationary points in stochastic bilevel optimization.
method Proposes F2{}^2SA-pp methods using ppth-order finite differences for hyper-gradient approximation.
result Achieves upper complexity bound of ildeO(pε4p/2) ilde{\mathcal{O}}(p ε^{-4-p/2}) for ppth-order smooth problems.

The paper defines and analyzes higher-order Yang-Mills-Higgs functionals and their gradient flows.

problem Analyzing the behavior of higher-order Yang-Mills-Higgs functionals and their gradient flows.
method Gauge fixing technique, L2L^2-bound of the Higgs field, local L2L^2-derivative estimates, energy estimates, blow-up analysis.
result Solutions to the gradient flow do not hit finite time singularities under certain conditions.

New method uses higher-order Langevin dynamics for efficient parallel sampling.

problem Efficient parallel sampling from high-dimensional log-concave distributions.
method Combines higher-order Langevin dynamics with blockwise Lagrange polynomial interpolation.
result Reduces the number of parallel points required for a target accuracy.

Users form information trails as they browse the web, checkin with a geolocation, rate items, or consume media. A common problem is to predict what a user might do next for the purposes of guidance, recommendation, or prefetching. First-order and higher-order Markov chains have been widely used methods to study such se…

2017-04-20abs ↗pdf ↗

Paper proves higher-order flow matching preserves optimality in generative modeling.

problem Theoretical guarantees for higher-order flow matching in generative modeling.
method Neural network approximations with controlled depth, width, and sparsity.
result Proves worst case optimality for second-order flow matching.

The paper proposes a method to compute higher infinitesimals in numerical and symbolic analysis.

problem Computing higher-order derivatives with higher infinitesimals.
method Automatic differentiation in terms of C-infinity rings and Weil algebras.
result A unifying theoretical framework for multivariate higher-order derivatives.

Improved algorithms for convex-concave min-max optimization and monotone variational inequalities.

problem Efficiently solving constrained convex-concave min-max problems and monotone variational inequalities.
method Higher-order methods achieving iteration complexities of O(1/T^{ rac{p+1}{2}}) for p-th order derivatives.
result Achieved improved convergence rates for min-max and monotone variational inequalities.

We prove several Liouville-type non-existence theorems for higher order Codazzi tensors and classical Codazzi tensors on complete and compact Riemannian manifolds, in particular. These results will be obtained by using theorems of the connections between the geometry of a complete smooth manifold and the global behavio…

2018-03-11abs ↗pdf ↗

Study on automorphisms of complex bkb^k-manifolds, extending previous work.

problem Investigate automorphisms of complex bkb^k-manifolds with higher-order degeneracies.
method Extend Mendoza's definition of complex bb-manifolds to complex bkb^k-manifolds and study their local and global automorphisms.
result Propose bkb^k-analogues for classical spaces of holomorphic functions.

New method improves DAG learning by using large coefficients for higher-order terms.

problem Recovering DAG structures from observational data is challenging due to combinatorial optimization.
method Proposes truncated matrix power iteration to approximate DAG constraints efficiently.
result Empirically outperforms previous methods by a factor of 3 or more in structural Hamming distance.

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.

It is shown that any finite list of smooth closed simply-connected 4-manifolds homeomorphic to a given one X can be obtained by removing a single compact contractible submanifold (or cork) from X, and then regluing it by powers of a boundary diffeomorphism. We then use this result to "separate" finite families of corks…

2019-02-07abs ↗pdf ↗

We obtain higher order estimates for a parabolic flow on a compact Hermitian manifold. As an application, we prove that a bounded ω^\hatω-plurisubharmonic solution of an elliptic complex Monge-Ampère equation is smooth under an assumption on the background Hermitian metric ω^\hatω. This generalizes a result of Székelyh…

2013-11-18abs ↗pdf ↗

New approach approximates c-space geometry of multi-loop linkages.

problem Higher-order mobility analysis of multi-loop linkages.
method Higher-order Taylor series expansion of geometric constraint mapping using joint screws.
result Local approximation of c-space and configurations with certain rank.

The study constructs a Legendrian cycle for FnW2,nF_nW^{2,n}-sets and proves Reilly-type variational formulae.

problem Understanding higher-order mean curvature integrals of non-smooth sets.
method Construction of a Legendrian cycle and analysis of proximal unit normal bundles.
result Reilly-type variational formulae for higher-order mean curvature integrals of FnW2,nF_nW^{2,n}-sets.

This paper examines how Higher-Order Langevin Dynamics reduces memorization in diffusion models.

problem Memorization of training samples in diffusion models, violating copyright and privacy.
method Introduces Higher-Order Langevin Dynamics (HOLD) to regularize diffusion model trajectories.
result The dynamics of the data variable in HOLD are governed by a low-pass-filtered version of the learned score function, with smoothness increasing with model order.

We generalize the Manolescu-Owens smooth concordance invariant delta(K) of knots K in the 3-sphere to invariants delta_{p^n}(K) obtained by considering covers of order p^n, with p prime. Our main result shows that for any odd prime p, the direct sum of delta_{p^n} as n ranges through the natural numbers, yields a homom…

2008-09-05abs ↗pdf ↗

Smooth activations enable optimal error rates in neural networks for Sobolev function classes.

problem Achieving optimal approximation and estimation error rates for neural networks in Sobolev function classes.
method Study of neural networks with smooth activations, proving optimal rates via approximation and statistical properties.
result Constant-depth networks with smooth activations achieve optimal rates of approximation and estimation, demonstrating smoothness adaptivity.

First order discretizations of Langevin diffusion can achieve better generalization error with additional smoothness assumptions.

problem Analyzing generalization error for first order discretizations of Langevin diffusion.
method Providing a sufficient smoothness condition to show that first order methods can achieve arbitrarily runtime complexity for a given expected generalization error.
result First order methods can achieve arbitrarily runtime complexity with additional smoothness assumptions.

For each sequence of polynomials, P=(p_1(t),p_2(t),...), we define a characteristic series of groups, called the derived series localized at P. Given a knot K in S^3, such a sequence of polynomials arises naturally as the orders of certain submodules of the sequence of higher-order Alexander modules of K. These group s…

2009-06-07abs ↗pdf ↗

For certain classes of knots we define geometric invariants called higher-order genera. Each of these invariants is a refinement of the slice genus of a knot. We find lower bounds for the higher-order genera in terms of certain von Neumann ρρ-invariants, which we call higher-order signatures. The higher-order genera o…

2008-07-02abs ↗pdf ↗

We define a family of functionals generalizing the Yang-Mills functional. We study the corresponding gradient flows and prove long-time existence and convergence results for subcritical dimensions as well as a bubbling criterion for the critical dimensions. Consequently, we have an alternate proof of the convergence of…

2015-05-26abs ↗pdf ↗

Given a compact manifold NnN^n, an integer kNk \in \mathbb{N}_* and an exponent 1p<1 \le p < \infty, we prove that the class C(Qm;Nn)C^\infty(\overline{Q}^m; N^n) of smooth maps on the cube with values into NnN^n is dense with respect to the strong topology in the Sobolev space Wk,p(Qm;Nn)W^{k, p}(Q^m; N^n) when the homotopy group $π_…

2012-03-16abs ↗pdf ↗

A fundamental property of complex networks is the tendency for edges to cluster. The extent of the clustering is typically quantified by the clustering coefficient, which is the probability that a length-2 path is closed, i.e., induces a triangle in the network. However, higher-order cliques beyond triangles are crucia…

2017-04-12abs ↗pdf ↗

We introduce a notion of geodesic curvature kζk_ζ for a smooth horizontal curve ζζ in a three-dimensional contact sub-Riemannian manifold, measuring how much a horizontal curve is far from being a geodesic. We show that the geodesic curvature appears as the first corrective term in the Taylor expansion of the sub-Riem…

2019-10-29abs ↗pdf ↗

Smooth manifolds have been always understood intuitively as spaces with an affine geometry on the infinitesimal scale. In Synthetic Differential Geometry this can be made precise by showing that a smooth manifold carries a natural structure of an infinitesimally affine space. This structure is comprised of two pieces o…

2018-09-16abs ↗pdf ↗