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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.

169,051 papers · 148 categories

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48 results for maximal distortion

Optimal insurance strategy for maximizing RDEU under various premium principles.

problem Maximizing a risk-averse individual's RDEU with insurance priced by a distortion-deviation principle.
method Proved necessary and sufficient conditions for the optimal solution, considered ambiguity orders, and analyzed specific examples.
result Conditions for no insurance or deductible insurance to be optimal.

The Madry Lab recently hosted a competition designed to test the robustness of their adversarially trained MNIST model. Attacks were constrained to perturb each pixel of the input image by a scaled maximal LL_\infty distortion εε = 0.3. This discourages the use of attacks which are not optimized on the LL_\infty dis…

2017-10-30abs ↗pdf ↗

Study calculates the modulus of Korányi ellipsoidal rings in Heisenberg groups.

problem Calculating the modulus of Korányi ellipsoidal rings in Heisenberg groups.
method Using a linear contact map in the Heisenberg group, the study proves the modulus formula.
result The modulus of Korányi ellipsoidal rings is derived with a specific formula.

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

problem Behavioral distortions in probability weighting affect portfolio optimization under different return distributions.
method Developed a unified framework to extract probability weighting functions from optimal portfolios modeled under Gaussian and NIG distributions.
result Increasing tail fatness amplifies behavioral distortions, and shifts in risk-free rates alter the curvature of these distortions.

Study models weather index insurance pricing by insurers and farmers, finding flexible pricing kernels boost profits.

problem Monopoly pricing of weather index insurance with risk and flexibility considerations.
method Bowley-type sequential game with insurer and farmer, using neural networks for farmer's payoff.
result Flexible pricing kernels increase insurer profits closer to indemnity insurance levels.

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

problem Tackles robustness of distortion risk measures under distributional uncertainty.
method Introduces new uncertainty sets and derives closed-form expressions for risk maximization.
result Derives closed-form expressions for risk maximization over uncertainty sets.

This paper improves monaural source enhancement using SDR as an objective function.

problem Maximizing signal-to-distortion ratio (SDR) for better monaural source enhancement.
method Uses signal-to-distortion ratio (SDR) as an objective function to improve monaural source enhancement.
result The proposed method achieved better performance than conventional methods.

Study on costs of manipulating AMM-based price oracles.

problem Cost of manipulation in AMM-based on-chain price oracles.
method Analyzes the robustness of AMM-based oracles to strategic manipulation, considering different aggregation methods and market conditions.
result Manipulation costs depend on the total quote depth and can be minimized by optimal liquidity weights.

Maximal distortion between geodesic and Euclidean diameters in polygonal domains is studied.

problem Maximal ratio of geodesic to Euclidean diameters in polygonal domains with holes.
method Analyzes convex polygons with holes, using geometric triangulations as a comparison.
result The supremum of the ratio is between Ω(h1/3)Ω(h^{1/3}) and O(h1/2)O(h^{1/2}) for convex polygons.

A framework compares image representations based on local geometry.

problem Comparing image representations based on global structure overlooks local differences.
method Quantify local geometry using Fisher information matrix and optimize differentiation with principal distortions.
result Identifies differences in local sensitivities between models.

Study homeomorphism groups of ordinals, proving strong distortion and normal generators.

problem Understanding algebraic and geometric properties of homeomorphism groups of ordinals.
method Analyzing successor ordinals with connections to permutation groups and manifolds.
result Proves strong distortion and normal generators for homeomorphism groups of ordinals.

MadNet uses MAD optimization to enhance deep model robustness against adversarial attacks.

problem Defending deep models against adversarial attacks.
method Inspired by certificate defense, MAD optimization increases separability of class clusters and decreases sensitivity to small distortions.
result MadNet improves adversarial robustness compared to state-of-the-art methods.

This paper solves a financial portfolio selection problem in incomplete markets.

problem Portfolio selection in incomplete financial markets with ambiguity.
method Constructing an efficient frontier, simplifying the problem, introducing a new distorted Legendre transformation, and proving the bipolar relation and distorted duality theorem.
result The existence and uniqueness of optimal strategies are shown for different utility functions under specific conditions.

Optimizes portfolio growth rate for a behavioral investor considering terminal relative growth rate.

problem Optimizing a behavioral investor's portfolio growth rate under relative growth criterion.
method Martingale method, concavification, and quantile optimization techniques.
result Derives closed-form optimal growth rate and finds significant impact of benchmark growth rate.

We consider the problem of distortion minimal morphing of nn-dimensional compact connected oriented smooth manifolds without boundary embedded in Rn+1\R^{n+1}. Distortion involves bending and stretching. In this paper, minimal distortion (with respect to stretching) is defined as the infinitesimal relative change in vol…

2006-05-25abs ↗pdf ↗

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

problem Calculating risk measures for sums of two counter-monotonic risks.
method Using a fixed distortion function and expressing the risk measure of a sum as the sum of two related measures of the marginals.
result The risk measure of a sum of two counter-monotonic risks can be expressed as the sum of two related distortion risk measures of the marginals.

A new family of stochastic dominance orders based on distortion functions.

problem Determining a continuum of dominance relations for risk assessment.
method Introducing H-distorted stochastic dominance, a generalized family of stochastic orders.
result Power-distorted stochastic dominance is particularly appealing due to its simplicity and statistical interpretations.

The distortion of a curve measures the maximum arc/chord length ratio. Gromov showed any closed curve has distortion at least pi/2 and asked about the distortion of knots. Here, we prove that any nontrivial tame knot has distortion at least 5pi/3; examples show that distortion under 7.16 suffices to build a trefoil kno…

2004-09-22abs ↗pdf ↗

CRCCA framework improves non-linear CCA with compressed representations.

problem Non-linear CCA for multi-view data with limited samples.
method Information-theoretic compressed representation framework (CRCCA) based on lattice quantization.
result The CRCCA framework provides theoretical bounds and optimality conditions, offering a flexible and computationally efficient solution.

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

problem Developing risk measures under random distortions of capacities.
method Introducing and analyzing randomly distorted Choquet integrals with respect to a distorted capacity, establishing properties and providing representations.
result Representation of comonotonic additive conditional risk measures using G-randomly distorted Choquet integrals.

We show that an entire branched cover of finite distortion cannot have a compact branch set if its distortion satisfies a certain asymptotic growth condition. We furthermore show that this bound is strict by constructing an entire, continuous, open and discrete mapping of finite distortion which is piecewise smooth, ha…

2017-09-25abs ↗pdf ↗

New study shows tradeoffs between compression quality, distortion, and perception.

problem Optimizing compression for low distortion often sacrifices perceptual quality.
method Adopted Blau & Michaeli's perceptual quality definition and studied the rate-distortion-perception tradeoff.
result Restricting perceptual quality to high generally requires a trade-off between rate and distortion.

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

problem Understanding distortion in virtually special groups containing free subgroups.
method Constructing examples of virtually special groups with finite rank free subgroups.
result Distortion functions grow like exp^k(x^m) and can be superexponential.

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

problem Designing lossy data compression schemes and comparing them with theoretical limits.
method Re-formulate rate-distortion objective and solve using neural networks.
result NERD accurately estimates the rate-distortion function for real-world datasets.

Introduces new performance criteria for investment under distorted probabilities.

problem Reconciling time-consistent performance with probability distortions.
method Two definitions of forward rank-dependent criteria, equivalence established; characterization of viable probability distortion processes.
result Characterization of optimal wealth process and new distorted measure.

Introduces a new conditional expectation under distorted probabilities, addressing time-inconsistency.

problem Time-inconsistency in nonlinear expectations under probability distortion.
method Localizes probability distortion and constructs a time-consistent conditional expectation.
result Constructs a conditional expectation that is time-consistent and corresponds to a parabolic differential equation.

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

problem Constructing adversarial examples that minimize visual distortion in a black-box threat model.
method Learning the noise distribution of adversarial examples to approximate the gradient of a non-differentiable loss function.
result The proposed attack results in much lower visual distortion compared to state-of-the-art black-box attacks.

Boundary effects inflate variance in Gaussian processes, leading to acquisition bias.

problem Boundary-induced acquisition bias in Gaussian processes.
method Traced root cause to geometric mechanism of kernel truncation at domain boundaries.
result Boundary effects create distortion that worsens with dimensionality, affecting acquisition behavior.

Study dynamic risk measures and performance indices using distortion functions.

problem Investigate time consistency of dynamic risk measures and performance indices generated by distortion functions.
method Analyze dynamic coherent risk measures (DCRMs) and dynamic weighted value at risk measures, proving their equivalence. Establish properties of families of DCRMs generated by distortion functions and define corresponding dynamic coherent acceptability indices (DCAIs). Examine time consistency of DCRMs and DCAIs.
result DCRM generated by distortion functions are sub-martingale time consistent but not super-martingale time consistent and not weakly acceptance time consistent.

This paper studies the problem of optimal investment with CRRA (constant, relative risk aversion) preferences, subject to dynamic risk constraints on trading strategies. The market model considered is continuous in time and incomplete. the prices of financial assets are modeled by Itô processes. The dynamic risk constr…

2011-06-09abs ↗pdf ↗