arXiv research

Convexity properties are preserved under radial transformations in hyperbolic and spherical geometries.

Random walks on free groups reveal asymmetric expansion factors.

The paper prices weather contracts using a complex temperature model.

New method recovers signals from compressed measurements using generative networks with contractive layers.

RSHT algorithm simplifies complex shapes to points.

In this paper we propose a closed-form approximation for the price of basket options under a multivariate Black-Scholes model, based on Taylor expansions and the calculation of mixed exponential-power moments of a Gaussian distribution. Our numerical results show that a second order expansion provides accurate prices o…

Improved online learning for fuzzy min-max neural networks.

Convergence of the Kalman filter is best analyzed by studying the contraction of the Riccati map in the space of positive definite (covariance) matrices. In this paper, we explore how this contraction property relates to a more fundamental non-expansiveness property of filtering maps in the space of probability distrib…

Proves DCNNs with expansive convolution are strongly universally consistent.

This paper extends Lie algebra contractions to infinite-dimensional spaces for better understanding of group limits.

Dropout increases the generalization of neural networks by expanding the weight space.

We fit the volatility fluctuations of the S&P 500 index well by a Chi distribution, and the distribution of log-returns by a corresponding superposition of Gaussian distributions. The Fourier transform of this is, remarkably, of the Tsallis type. An option pricing formula is derived from the same superposition of Black…

Simultaneous inference after model selection is of critical importance to address scientific hypotheses involving a set of parameters. In this paper, we consider high-dimensional linear regression model in which a regularization procedure such as LASSO is applied to yield a sparse model. To establish a simultaneous pos…

Maximal concentration bounds for stochastic approximation with heavy-tailed noise.

Valuing FF contracts in time-dependent models

The paper improves energy contract pricing models by incorporating jumps and varying parameters.

New analysis of stochastic approximation with non-expansive mappings.

In this paper we present a new methodology for option pricing. The main idea consists to represent a generic probability distribution function (PDF) via a perturbative expansion around a given, simpler, PDF (typically a gaussian function) by matching moments of increasing order. Because, as shown in literature, the pri…

We offer new formulas for European option pricing under tempered stable processes.

Paper proposes new methods for improving interatomic potentials.

Bayesian methods estimate regression functions on submanifolds using graph Laplacian eigenbasis.

Improved stochastic approximation method reduces residual error.

This work proposes hyperbolic deep convolutional neural networks for better pattern recognition.

We introduce a fully coherent spin network amplitude whose expansion generates all SU(2) spin networks associated with a given graph. We then give an explicit evaluation of this amplitude for an arbitrary graph. We show how this coherent amplitude can be obtained from the specialization of a generating functional obtai…

The study optimizes Gaussian process approximations for finite-rank models.

Study asymptotic expansion of graph Laplacian on discretized surfaces, relating spanning trees and cycle-rooted forests.

Study semiclassical measures on complex hyperbolic quotients, identifying measure supports.

We consider geometric flows of hypersurfaces expanding by a function of the extrinsic curvature and we show that the homothethic sphere is the unique solution of the flow which converges to a point at the initial time. The result does not require assumptions on the speed other than positivity and monotonicity and it is…

Two new algorithms solve nonconvex-strongly concave problems efficiently.

In this paper we study the pricing of exchange options under a dynamic described by stochastic correlation with random jumps. In particular, we consider a Ornstein-Uhlenbeck covariance model with Levy Background Noise Process driven by Inverse Gaussian subordinators. We use expansion in terms of Taylor polynomials and …

Proves transitivity of real Anosov diffeomorphisms with specific properties.

CCDF reduces diffusion sampling steps for inverse problems.

Study finds public procurement awards, especially NGEU-funded ones, boost new lending.

The paper transforms a convex hull into a concave surface around a point cloud.

Study of Brown--York mass for four-dimensional asymptotically flat manifolds.

We calculate the optimal solutions of the fully heterogeneous Von Neumann expansion problem with $N$ processes and $P$ goods in the limit $N\to\infty$. This model provides an elementary description of the growth of a production economy in the long run. The system turns from a contracting to an expanding phase as $N$ in…

Holomorphic automorphisms on hyperkähler manifolds with high entropy are Kummer examples.

The paper explores coalescent contractions in contractible spaces, providing criteria and examples.

The study characterizes homology 4-manifolds with $g_2\leq 5$ combinatorially.

Rescaling expansiveness proven for k*-expansive vector fields.

The asymptotic concentration of the Fr{é}chet mean of IID random variables on a Rieman-nian manifold was established with a central limit theorem by Bhattacharya \& Patrangenaru (BP-CLT) [6]. This asymptotic result shows that the Fr{é}chet mean behaves almost as the usual Euclidean case for sufficiently concentrated di…

Machine learning predicts US and EuroZone business cycles with high accuracy.

Computable contracts simplify financial transactions and reduce legal costs.

In an online contract selection problem there is a seller which offers a set of contracts to sequentially arriving buyers whose types are drawn from an unknown distribution. If there exists a profitable contract for the buyer in the offered set, i.e., a contract with payoff higher than the payoff of not accepting any c…

The paper derives expansions for Green's operators and resolvents using Hadamard methods.

Optimal execution strategy for merger & acquisition contracts with price impact.

This paper develops a method to select a reference contract for multi-contract quoting to minimize execution risk.

Proposes a probabilistic framework for smart contract risk quantification.