arXiv research

This paper shows how to calculate risk measures for sums of two counter-monotonic risks.

Study dynamic risk measures and performance indices using distortion functions.

Estimates rate-distortion function for large datasets using neural networks.

Computed distortion coefficients for the α-Grushin plane.

New coding theorem shows achievable rate matches theoretical limit.

We study a generalized family of stochastic orders, semiparametrized by a distortion function H, namely H-distorted stochastic dominance, which may determine a continuum of dominance relations from the first- to the second-order stochastic dominance (and beyond). Such a family is especially suitable for representing a …

The study shows exponential distortion in virtually special groups containing free subgroups.

Study on risk measures using distorted Choquet integrals with random distortions.

We discuss two distinct approaches, for distorting risk measures of sums of dependent random variables, which preserve the property of coherence. The first, based on distorted expectations, operates on the survival function of the sum. The second, simultaneously applies the distortion on the survival function of the su…

Modified BA algorithm computes RD and DR functions efficiently.

We propose computationally efficient encoders and decoders for lossy compression using a Sparse Regression Code. The codebook is defined by a design matrix and codewords are structured linear combinations of columns of this matrix. The proposed encoding algorithm sequentially chooses columns of the design matrix to suc…

Sharp bounds for distortion risk metrics under uncertain distributions.

Paper proposes robust risk measures for non-negative risks with partial information.

The study finds minimal distortion embeddings of surfaces into small domains.

Let $M$ and $N$ be compact smooth oriented Riemannian $n$-manifolds without boundary embedded in $\mathbb{R}^{n+1}$. Several problems about minimal distortion bending and morphing of $M$ to $N$ are posed. Cost functionals that measure distortion due to stretching or bending produced by a diffeomorphism $h:M \to N$ are …

Paper introduces new risk norms based on ES with flexible distortion functions.

New method for risk quantification using quantile processes and measure distortions.

DP-means clustering was obtained as an extension of $K$-means clustering. While it is implemented with a simple and efficient algorithm, it can estimate the number of clusters simultaneously. However, DP-means is specifically designed for the average distortion measure. Therefore, it is vulnerable to outliers in data, …

The paper studies robust risk measures with linear penalties under uncertain distributions.

The problem behind this paper is the proper measurement of the degree of quality/acceptability/distance to arbitrage of trades. We are narrowing the class of coherent acceptability indices introduced by Cherny and Madan (2007) by imposing an additional mathematical property. For this, we introduce the notion of a conca…

We solve the vector embedding problem by minimizing total distortion under constraints.

Paper studies fundamental limits of communication in distributed learning.

New bounds for optimal transport using Gaussian processes and rate-distortion functions.

Paper derives best- and worst-case GlueVaR measures with incomplete data.

Given a space $Y$ in $X$, a cycle in $Y$ may be filled with a chain in two ways: either by restricting the chain to $Y$ or by allowing it to be anywhere in $X$. When the pair $(G,H)$ acts on $(X, Y)$, we define the $k$-volume distortion function of $H$ in $G$ to measure the large-scale difference between the volumes of…

Study the tradeoff between signal distortion and human perception over finite channels.

Paper proposes a new black-box attack approach to minimize visual distortion.

The paper analyzes worst-case distortion risk metrics and weighted entropy under partial information.

We produce examples of codimension one foliations of the Euclidean and hyperbolic planes with bounded geometry which are topologically products, but for which leaves are non-recursively distorted. That is, the function which compares intrinsic distances in leaves with extrinsic distances in the ambient space grows fast…

Predictive rate-distortion analysis suffers from the curse of dimensionality: clustering arbitrarily long pasts to retain information about arbitrarily long futures requires resources that typically grow exponentially with length. The challenge is compounded for infinite-order Markov processes, since conditioning on fi…

Study optimal reinsurance contracts to prevent moral hazard under non-concave premium principles.

Framework uses IRL and RL to elicit and optimize risk preferences robustly to noise.

Distortion (Denneberg 1990) is a well known premium calculation principle for insurance contracts. In this paper, we study sensitivity properties of distortion functionals w.r.t. the assumptions for risk aversion as well as robustness w.r.t. ambiguity of the loss distribution. Ambiguity is measured by the Wasserstein d…

Given a finite metric CW complex $X$ and an element $α\in π_n(X)$, what are the properties of a geometrically optimal representative of $α$? We study the optimal volume of $kα$ as a function of $k$. Asymptotically, this function, whose inverse, for reasons of tradition, we call the volume distortion, turns out to be an…

Researchers prove inner product recovery is impossible in latent space models.

ReLU networks don't exponentially distort curve lengths as previously thought.

The paper integrates behavioral distortions into portfolio optimization using implied probability weighting functions.

Investigates stability of Epstein-Zin problem under market distortions.

New method estimates rate-distortion function using optimal transport.

Within the framework of the cumulative prospective theory of Kahneman and Tversky, this paper considers a continuous-time behavioral portfolio selection problem whose model includes both running and terminal terms in the objective functional. Despite the existence of S-shaped utility functions and probability distortio…

Paper quantifies distortion risk measures' robustness to distributional uncertainty.

We prove that the distortion function of the Gauss map of a harmonic surface coincides with the distortion function of the surface. Consequently, Gauss map of a harmonic surface is ${\mathcal{K}}$ quasiregular if and only if the surface is ${\mathcal{K}}$ quasiregular, provided that the Gauss map is regular or what is …

This paper studies communication efficiency in federated learning by optimizing the sum-rate-distortion function for indirect multiterminal source coding.

Distortion risk measures are extensively used in finance and insurance applications because of their appealing properties. We present three methods to construct new class of distortion functions and measures. The approach involves the composting methods, the mixing methods and the approach that based on the theory of c…

We introduce the concept of forward rank-dependent performance processes, extending the original notion to forward criteria that incorporate probability distortions. A fundamental challenge is how to reconcile the time-consistent nature of forward performance criteria with the time-inconsistency stemming from probabili…

In this paper, we consider the problem of optimal reinsurance design, when the risk is measured by a distortion risk measure and the premium is given by a distortion risk premium. First, we show how the optimal reinsurance design for the ceding company, the reinsurance company and the social planner can be formulated i…

A morph between two Riemannian $n$-manifolds is an isotopy between them together with the set of all intermediate manifolds equipped with Riemannian metrics. We propose measures of the distortion produced by some classes of morphs and diffeomorphisms between two isotopic Riemannian $n$-manifolds and, with respect to th…

Vertex distortion detects if a knot is unknot.