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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.

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48 results for Nash entropy

Proposes a new criterion for selecting Nash equilibria considering both utility and inequality.

problem Finding a fair Nash equilibrium in group decision-making.
method Introduces entropy-norm space for geometric selection of strict Nash equilibria.
result The closest entropy-norm pair to the largest entropy-norm pair in rescaled space is the most suitable equilibrium.

Ancient Ricci flows with bounded Nash entropy have uniform Sobolev inequalities.

problem Bounding Nash entropy in ancient Ricci flows.
method Uniformly bounded Nash entropy implies uniform bounds on the ν-functional, leading to uniform logarithmic and Sobolev inequalities.
result Uniform logarithmic and Sobolev inequalities on ancient Ricci flows with bounded Nash entropy.

Algorithm learns Nash equilibria in stochastic games using entropy-regularized policies.

problem Learning Nash equilibria in zero-sum stochastic games is computationally expensive.
method Entropy-regularized soft policies for Q-function updates.
result Algorithm converges to Nash equilibrium under certain conditions.

Compact RCD spaces derived from singular Kahler metrics on 3D projective varieties.

problem Understanding geometric structures of singular Kahler spaces.
method Proving RCD spaces homeomorphic to 3D projective varieties with bounded Nash entropy and Ricci curvature.
result Compact RCD spaces are equivalent to underlying projective varieties.

The article examines entropy-information inequalities for continuous-time Markov chains under curvature-dimension conditions.

problem Proving Li-Yau inequalities and modified logarithmic Sobolev inequalities for reversible Markov chains.
method Introducing the CDΥ(κ,F)CD_Υ(κ,F) condition and deriving entropy-information inequalities.
result Derives functional inequalities relating entropy to Fisher information.

Let (Mn,g)(M^n, g) be a complete Riemannian manifold with RcKgRc\geq -Kg, H(x,y,t)H(x, y, t) is the heat kernel on MnM^n, and H=(4πt)n2efH= (4πt)^{-\frac{n}{2}}e^{-f}. Nash entropy is defined as N(H,t)=Mn(fH)dμ(x)n2N(H, t)= \int_{M^n} (fH) dμ(x)- \frac{n}{2}. We studied the asymptotic behavior of N(H,t)N(H, t) and t[N(H,t)]\frac{\partial}{\partial t}\Big[N(H, t)\Big]

2012-09-28abs ↗pdf ↗

Ancient Ricci flows with asymptotic solitons have uniform bounds and inequalities.

problem Bounding and understanding ancient Ricci flows with asymptotic solitons.
method Analyzing asymptotic solitons, proving uniform bounds on Perelman's ν-functional, and showing Nash entropy bounds.
result Uniform bounds on Perelman's ν-functional and logarithmic/Sobolev inequalities for ancient solutions.

PAPAL algorithm finds mixed Nash equilibria in continuous games.

problem Finding mixed Nash equilibria in non-convex, non-concave games.
method Particle-based Primal-Dual Algorithm (PAPAL) for weakly entropy-regularized min-max optimization.
result PAPAL offers non-asymptotic convergence guarantees for εε-mixed Nash equilibrium.

Paper studies convergence of Mean-Field GDA dynamics for MNE of continuous games.

problem Finding mixed Nash equilibria in continuous games.
method Two-scale Mean-Field Gradient Descent Ascent dynamics.
result Two-scale Mean-Field GDA converges exponentially to MNE without convexity assumptions.

Let MM and NN be Nash manifolds, and ff and gg Nash maps from MM to NN. If MM and NN are compact and if ff and gg are analytically R-L equivalent, then they are Nash R-L equivalent. In the local case, CinftyC^infty R-L equivalence of two Nash map germs implies Nash R-L equivalence. This shows a difference of Nash…

2010-04-23abs ↗pdf ↗

Machine learning detects NASH patients from medical claims data.

problem Detecting undiagnosed NASH patients for screening and management.
method Gradient-boosted decision trees trained on administrative medical claims data.
result Model precision for NASH detection is significantly higher than NASH incidence.

The paper examines Nash equilibrium in GANs for stationary Gaussian processes.

problem Existence and uniqueness of Nash equilibrium in GANs for stationary Gaussian processes.
method Analyzes the existence of Nash equilibrium in GANs for stationary Gaussian processes, considering different discriminator families.
result The existence of Nash equilibrium depends on the discriminator family and symmetry properties of the generator family.

A Nash game theory approach allocates capital requirements among financial institutions.

problem Allocating systemic risk measures among financial institutions.
method Proposes a Nash allocation rule inspired by game theory.
result Provides sufficient conditions for the existence and uniqueness of Nash allocation rules.

In this paper we review our earlier work on quantum computing and the Nash Equilibrium, in particular, tracing the history of the discovery of new Nash Equilibria and then reviewing the ways in which quantum computing may be expected to generate new classes of Nash equilibria. We then extend this work through a substan…

2007-07-03abs ↗pdf ↗

This paper simplifies the Nash Bargaining Solution for use in intellectual property cases.

problem Limited application of Nash Bargaining Solution in assigning intellectual property damages.
method Normalizes the Nash Bargaining Solution and provides a methodology for determining bargaining weight.
result Clarifies the application of Nash Bargaining Solution to specific case facts.

The study examines Nash equilibria in utility maximization games with multiplicative performance criteria.

problem Existence and uniqueness of Nash equilibria in multiplicative performance criteria games.
method General characterization of Nash equilibria for a large class of utility functions.
result Existence and uniqueness of Nash equilibria for arbitrary initial wealth vectors.

We obtain global extensions of the celebrated Nash-Kuiper theorem for C1,θC^{1,θ} isometric immersions of compact manifolds with optimal Hölder exponent. In particular for the Weyl problem of isometrically embedding a convex compact surface in 3-space, we show that the Nash-Kuiper non-rigidity prevails upto exponent $θ<1…

2019-06-20abs ↗pdf ↗

Improved SEG method converges to Nash equilibrium in bilinear games.

problem Stochastic bilinear minimax optimization problem
method Stochastic ExtraGradient (SEG) method with constant step size, iteration averaging, and scheduled restarting.
result Provable convergence to Nash equilibrium under standard settings, optimal convergence rate in interpolation setting.

This research uses reinforcement learning to find optimal emission offsets in greenhouse gas markets.

problem Finding optimal emission offsets in greenhouse gas markets to control excess emissions.
method Utilized reinforcement learning, specifically Nash-DQN, to estimate market Nash equilibria.
result Emitting firms can achieve significant financial savings by abiding by the Nash equilibria found in the market.

Study Nash equilibrium in mean field portfolio games with random market parameters.

problem Modeling wealth and relative performance in competitive financial markets.
method Martingale optimality principle approach to characterize Nash equilibrium in mean field FBSDE.
result Unique Nash equilibrium found under weak interaction assumption and market parameters independence.

A new algorithm reduces memory and computational needs for reinforcement learning.

problem Memory and computational inefficiency in model-free reinforcement learning.
method Memory-Efficient Nash Q-Learning (ME-Nash-QL) for two-player zero-sum games.
result Proves ME-Nash-QL reduces space and sample complexity for tabular and long-horizon cases.

We introduce a new loss function for evaluating forecasts and estimate models using it.

problem Lack of a decision-theoretic foundation for evaluating forecasts using the Nash-Sutcliffe efficiency.
method We introduce and analyze the Nash-Sutcliffe loss function and its application in estimating models.
result Nash-Sutcliffe loss provides a decision-theoretic foundation for evaluating and estimating models.