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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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48 results for Relative entropy

Extends specific relative entropy to multidimensional continuous martingales.

problem Mutual singularity of martingale laws in continuous time.
method Extension of specific relative entropy from one to multiple dimensions, including closed-form expressions for simple examples.
result Establishes that the lower bound on specific relative entropy from Gantert carries over to higher dimensions and is tight.

Entropy asymmetry affects regularization in ERM, leading to biased solutions.

problem Analyzing the impact of relative entropy asymmetry in ERM regularization.
method Examined Type-I and Type-II ERM-RER, comparing their solutions and properties.
result Type-II ERM-RER regularization introduces a strong bias against training data.

A measure called relative cluster entropy distinguishes between correlated and uncorrelated sequences.

problem Distinguishing between sequences with different correlation degrees.
method Minimum relative entropy principle applied to cluster partitions of power-law correlated sequences.
result Optimal Hurst exponents are selected for market price series, indicating non-markovianity.

We define a relative entropy for two expanding solutions to mean curvature flow of hypersurfaces, asymptotic to the same cone at infinity. Adapting work of White and using recent results of Bernstein and Bernstein-Wang, we show that expanders with vanishing relative entropy are unique in a generic sense. This also impl…

2018-12-20abs ↗pdf ↗

New statistical test for change-point detection using relative entropy.

problem Offline change-point detection using divergence metrics.
method Study of empirical relative entropy distributions, derivation of approximations, introduction of new Berry-Esseen bounds.
result Theoretical and practical validation of relative entropy for change-point detection.

Inference for normal and Monte Carlo distributions using minimum relative entropy.

problem Inference from partial information on expectations and covariances.
method Minimum relative entropy sub-manifolds, analytical formulas, Monte Carlo simulations.
result Improved numerical implementation for inference from partial information.

The notion of utility maximising entropy (u-entropy) of a probability density, which was introduced and studied by Slomczynski and Zastawniak (Ann. Prob 32 (2004) 2261-2285, arXiv:math.PR/0410115 v1), is extended in two directions. First, the relative u-entropy of two probability measures in arbitrary probability space…

2007-09-09abs ↗pdf ↗

New regularization method reduces support of empirical risk minimization solutions.

problem Regularization in empirical risk minimization with relative entropy.
method Introduces Type-II regularization, characterizes solutions, analyzes properties of relative entropy.
result Type-II regularization collapses solution support into reference measure's support.

We introduce a class of generalized relative entropies (inspired by the Bregman divergence in information theory) on the Wasserstein space over a weighted Riemannian or Finsler manifold. We prove that the convexity of all the entropies in this class is equivalent to the combination of the nonnegative weighted Ricci cur…

2011-12-23abs ↗pdf ↗

We investigate the mm-relative entropy, which stems from the Bregman divergence, on weighted Riemannian and Finsler manifolds. We prove that the displacement KK-convexity of the mm-relative entropy is equivalent to the combination of the nonnegativity of the weighted Ricci curvature and the KK-convexity of the weig…

2010-05-08abs ↗pdf ↗

A qq-Gaussian measure is a generalization of a Gaussian measure. This generalization is obtained by replacing the exponential function with the power function of exponent 1/(1q)1/(1-q) (q1q\neq 1). The limit case q=1q=1 recovers a Gaussian measure. For 1q<31\leq q <3, the set of all qq-Gaussian densities over the real line …

2020-02-06abs ↗pdf ↗

Study quantifies information flow in neural networks using relative entropy and RG analogy.

problem Quantifying information flow in deep neural networks.
method Explicit computation of relative entropy in Ising models and feedforward neural networks.
result Monotonic increase of relative entropy to an asymptotic value, confirming connection to c-theorem.

This paper optimizes trading strategies to minimize risk and maximize profit while accounting for market uncertainty.

problem Optimizing trading strategies to minimize risk and maximize profit while accounting for market uncertainty.
method Relative entropy-regularized robust optimal control problem, modeled as a stochastic differential game.
result Analytical expressions for optimal strategy and trajectory are derived under specific assumptions.

We introduce a pathwise approach to analyze the relative performance of an equity portfolio with respect to a benchmark market portfolio. In this energy-entropy framework, the relative performance is decomposed into three components: a volatility term, a relative entropy term measuring the distance between the portfoli…

2013-08-25abs ↗pdf ↗

A new method, REC, compresses images by encoding their latent representations efficiently.

problem Efficiently compressing single images with latent representations.
method Relative Entropy Coding (REC) that directly encodes latent representations with codelength close to relative entropy.
result REC is more efficient for single image compression compared to previous methods and is competitive for lossy compression.

Abstract: Necessary and sufficient conditions for gradient flows of relative entropy in Lindblad equations.

problem Conditions for gradient flows in finite-dimensional Lindblad equations.
method Analyzes conditions for a finite-dimensional Lindblad equation to have a gradient flow structure for the von Neumann relative entropy.
result A finite-dimensional Lindblad equation admits a gradient flow structure for the von Neumann relative entropy if and only if the BKM-detailed balance condition holds.

In this paper we focus on the uniqueness question for (expanding) solutions of the Harmonic map flow coming out of smooth 0-homogeneous maps with values into a closed Riemannian manifold. We introduce a relative entropy for two purposes. On the one hand, we prove the existence of two expanding solutions associated to a…

2018-06-30abs ↗pdf ↗

REMEDI improves neural entropy estimation across various tasks.

problem Challenges in estimating information theoretic quantities in high-dimensional data.
method Combines minimization of cross-entropy with estimation of deviation from data density.
result Improves accuracy in entropy estimation on synthetic and natural data.

The null energy condition is characterized via convexity of entropy in Lorentzian manifolds.

problem Characterizing the null energy condition in Lorentzian manifolds.
method Characterization via convexity of the relative entropy along displacement interpolations on null hypersurfaces.
result The null energy condition is characterized in terms of convexity of the relative entropy.

In his 2011 work, Maas has shown that the law of any time-reversible continuous-time Markov chain with finite state space evolves like a gradient flow of the relative entropy with respect to its stationary distribution. In this work we show the converse to the above by showing that if the relative law of a Markov chain…

2014-05-11abs ↗pdf ↗

New surface area measures defined for ball-convex bodies, leading to entropy and inequalities.

problem Defining and analyzing surface area measures for ball-convex bodies.
method Introducing LpL_p relative surface areas, proving invariance and inequalities, and using geometric interpretations.
result Established inequalities and a new notion of entropy for ball-convex bodies.

The paper extends entropy concepts to Monge-Ampère measures with prescribed singularities.

problem Investigating entropy for Monge-Ampère measures with specific singularities.
method Generalizing entropy for potentials, studying stability under blow-ups and perturbations, proving Moser-Trudinger inequalities.
result Functions with finite entropy belong to a specific energy class and maintain singularities of the model potential.

This paper strengthens the central limit theorem for order statistics using relative entropy.

problem Establishing a stronger mode of convergence for central limit behavior of order statistics.
method Using relative entropy to ensure a stronger mode of convergence for central limit behavior of order statistics.
result An order O(1/n)O(1/\sqrt{n}) rate of convergence is established under mild conditions.

New measure of maximal entropy found for a class of geometrically finite groups.

problem Finding a measure of maximal entropy for relatively Anosov groups.
method Constructing reparameterizations and using exponential expansion along unstable foliations.
result The Bowen-Margulis-Sullivan measure is finite and unique for relatively Anosov groups.

Paper develops a robust HVA measure for dynamic hedging under liquidity stress.

problem Valuation of dynamic hedging under liquidity stress.
method Defines robust HVA as worst-case expected loss over a relative-entropy neighborhood of loss distributions for no-trade bands.
result Wider no-trade bands lower rebalancing costs but increase hedge-error risk.

Study finds optimal martingale coupling between two distributions with minimal entropy.

problem Finding the optimal martingale coupling between two distributions with minimal relative entropy.
method Solving a dual problem to find the log-density of the optimal coupling, which represents the marginal and martingale constraints.
result The log-density of the optimal coupling is given by a triplet of real functions representing the marginal and martingale constraints.

Paper finds a new principle for optimizing consumption and wealth using Tsallis entropy.

problem Optimal consumption-investment problem with recursive utility.
method Established connection to quadratic BSDE, derived stochastic maximum principle.
result Proved existence of optimal strategy and analyzed coupled system.

This work tightens generalization error bounds using Wasserstein distance.

problem Improving expected generalization error bounds in machine learning.
method Introduces bounds based on Wasserstein distance for various settings.
result New, tighter bounds based on relative entropy and other information measures.

REGS samples from unnormalized distributions using gradient flow and neural networks.

problem Sampling from unnormalized distributions with high accuracy and efficiency.
method REGS is a particle method that iteratively transforms samples from a reference distribution to match an unnormalized target distribution using Wasserstein gradient flow and neural networks.
result REGS outperforms state-of-the-art methods in sampling from challenging multimodal distributions and real datasets.

New method uses asymmetric Tsallis relative entropy for better risk assessment in financial portfolios.

problem Improving risk assessment for financial portfolios using asymmetric data.
method Generalized Tsallis relative entropy (ATRE) for asymmetric distributions of returns.
result ATRE shows better risk-return profiles, especially during market crashes.

Study uses CSIE to estimate portfolio volatility relative to market.

problem Estimating relative volatility risk of stock portfolios.
method Cross-sectional intrinsic entropy (CSIE) model to estimate cross-sectional volatility.
result Discover sets of symbols that outperform market indices in terms of return with similar or lower risk.

The study optimizes distribution estimation from samples with relative entropy error, adapting to sparse distributions.

problem Estimating discrete distributions with high-probability accuracy in relative entropy.
method Analysis of Laplace estimator and confidence-dependent smoothing techniques, including data-dependent smoothing.
result Optimal high-probability risk bounds for various estimators, including a new data-dependent smoothing method.

Improved sampling from complex distributions with reduced bias.

problem Reducing bias in high-dimensional sampling algorithms.
method Hierarchical entropy analysis to weaken assumptions and expand scope.
result Bias reduction in low-dimensional marginals scales with lower dimension, not full dimension.

Study of endperiodic maps on infinite graphs, proving homotopy and eigenvalue properties.

problem Understanding endperiodic maps on infinite graphs with finitely many ends.
method Adapting relative train track maps and combinatorial techniques to infinite type setting.
result Any generalized endperiodic map is homotopic to a relative train track map.

Study shows uniform-time chaos propagation in mean field Langevin dynamics.

problem Understanding the convergence of marginal distributions in mean field dynamics.
method Assumed functional convexity of energy, used LpL^p-convergence and Wasserstein metrics.
result Uniform-in-time propagation of chaos proved in both L2L^2-Wasserstein and relative entropy.