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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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112224336448 · Jun 202019922001200920172026
48 results for Linear Stability

We can talk about two kinds of stability of the Ricci flow at Ricci flat metrics. One of them is a linear stability, defined with respect to Perelman's functional F\mathcal{F}. The other one is a dynamical stability and it refers to a convergence of a Ricci flow starting at any metric in a neighbourhood of a considere…

2004-10-04abs ↗pdf ↗

We consider a modified Ricci flow equation whose stationary solutions include Einstein and Ricci soliton metrics, and we study the linear stability of those solutions relative to the flow. After deriving various criteria that imply linear stability, we turn our attention to left-invariant soliton metrics on (non-compac…

2013-09-24abs ↗pdf ↗

New proof of Schwarzschild stability using geometric gauge.

problem Linear stability of Schwarzschild spacetime under gravitational perturbations.
method Employing a new geometric gauge and exploiting the structure of transport equations.
result Established both orbital and asymptotic stability for linearised quantities.

Improved RL algorithm stabilizes unknown linear systems with polynomial regret.

problem Learning and stabilizing unknown linear dynamical systems.
method Proposes an algorithm with an improved exploration strategy for fast stabilization.
result Achieves ildeO(T) ilde{\mathcal{O}}(\sqrt{T}) regret after TT time steps.

Church-Ellenberg-Farb used the language of FI-modules to prove that the cohomology of certain sequences of hyperplane arrangements with S_n-actions satisfies representation stability. Here we lift their results to the level of the arrangements themselves, and define when a collection of arrangements is "finitely genera…

2016-03-28abs ↗pdf ↗

Paper proposes a new framework to improve stability-based bounds in deep learning.

problem Explaining generalization in overparameterized neural networks.
method Decomposes excess risk dynamics into signal and noise components, applying stability-based bounds only to the noise.
result The decomposition framework improves stability-based bounds and explains generalization in neural networks.

The paper proves stability for Einstein metrics with special twisted spinors.

problem Stability of Einstein metrics with specific spinor conditions.
method Proves linear semi-stability for a class of Einstein metrics with non-positive scalar curvature.
result Linear semi-stability for Einstein metrics carrying a parallel twisted spinr^r spinor.

Paper presents neural network controllers for offset-free setpoint tracking.

problem Offset-free setpoint tracking using neural network controllers.
method Exploiting slope-restricted activation functions, linear matrix inequalities are used to verify stability.
result Global and local stability conditions for neural network controllers are derived.

This work examines the stability of GD and SGD near minima, revealing nonlinear dynamics that differ from linear analysis.

problem The stability of optimization algorithms like GD and SGD near minima is not well understood.
method The authors derive an exact criterion for stable oscillations of GD near minima in the multivariate setting, considering high-order derivatives.
result Nonlinear dynamics can diverge in expectation even if a single batch is unstable, challenging linear analysis.

We construct analogues of FI-modules where the role of the symmetric group is played by the general linear groups and the symplectic groups over finite rings and prove basic structural properties such as Noetherianity. Applications include a proof of the Lannes--Schwartz Artinian conjecture in the generic representatio…

2014-08-16abs ↗pdf ↗

Study on stability of 3D sessile drops, identifying degenerate kernel.

problem Linear stability of three-dimensional sessile drops with a free contact line.
method Derived constrained second variation, formulated Jacobi problem, combined geometric and Fourier analysis.
result Kernel of the constrained Jacobi operator is exactly the space of horizontal translations under pressure-volume nondegeneracy.

Study shows how to control jump-diffusion processes with stable feedback controls in reinforcement learning.

problem Control jump-diffusion processes with unknown coefficients in reinforcement learning.
method Lipschitz continuous optimal feedback controls, stability analysis of forward-backward SDEs, least-squares algorithm.
result Achieves O(NlnN)O(\sqrt{N\ln N}) regret for linear-convex learning problems with jumps.

Modeling financial systemic risk with optimal control theory for stability.

problem Analyzing and stabilizing systemic risk in interconnected financial entities.
method Developed a theoretical model using optimal control theory, including steps for synthesizing stabilizing controllers.
result The model ensures that the HH^{\infty} norms of the mappings from disturbance to output are less than a predefined constant, stabilizing the system.

This paper analyzes how periodic and soft target updates stabilize linear Q-learning.

problem Theoretical explanation of stabilization mechanisms for linear Q-learning.
method Exact analysis using switched linear system dynamics and the joint spectral radius.
result Periodic and soft target updates can guarantee convergence to the exact projected Q-Bellman solution under specific conditions.

Proves stability of Schwarzschild black holes without symmetry assumptions.

problem Stability of Schwarzschild black holes under general conditions.
method Teleologically normalised double null gauges, analysis of linear stability, and control of non-linearities.
result Proves non-linear asymptotic stability of Schwarzschild family as solutions to Einstein vacuum equations.

Study identifies and validates a method for system identification of Markov jump linear systems.

problem System identification for autonomous Markov jump linear systems with complete state observations.
method Proposes switched least squares method for identification and derives rates of convergence.
result Data-independent rate of convergence is O(log(T)/T)\mathcal{O}\big(\sqrt{\log(T)/T} \big), showing strong consistency.

To date, the instability of prognostic predictors in a sparse high dimensional model, which hinders their clinical adoption, has received little attention. Stable prediction is often overlooked in favour of performance. Yet, stability prevails as key when adopting models in critical areas as healthcare. Our study propo…

2016-09-28abs ↗pdf ↗

New models learn stable latent clusters without side info.

problem Stability of non-linear ICA representations without side information.
method Deep generative models with latent clusterings, compared to standard VAEs and auxiliary labeled models.
result Deep generative models with latent clusterings are as stable as models with side information.

The paper proves stability for a modified Bach flow on various manifolds.

problem Stability of gauge-modified Bach flow on manifolds.
method Linear stability proved via spectral bounds and Koiso identity generalization. Nonlinear stability for hyperbolic and Poincaré-Einstein spaces.
result Linear and nonlinear stability results for the Bach flow on specific manifolds.

Study shows instability of Kähler Ricci solitons and stability of orbifold singularities.

problem Linear stability and instability of Kähler Ricci solitons.
method Extending the approach of \cite{chi04} and \cite{hm11}, via recent work \cite{cm21} on gradient shrinking Ricci solitons.
result Linear instability of the BCCD shrinking soliton and stability of orbifold singularities of Kähler solitons.

Improved stability analysis of neural network systems using Zames-Falb multipliers.

problem Analyzing stability of linear systems with neural network nonlinearities.
method Using integral quadratic constraints, sector-bounded and slope-restricted structure, and acausal Zames-Falb multipliers.
result Flexible and versatile framework for stability analysis with improved computational efficiency.

Bayesian algorithm stabilizes unknown continuous-time systems from unstable data.

problem Learning and stabilizing unknown continuous-time systems with uncertain dynamics.
method Bayesian learning algorithm that learns from unstable data to stabilize the system in finite time.
result The algorithm stabilizes unknown continuous-time stochastic linear systems effectively after a short time period.

As a step toward understanding the analytic behavior of Type-III Ricci flow singularities, i.e. immortal solutions that exhibit |Rm|<C/t curvature decay, we examine the linearization of an equivalent flow at fixed points discovered recently by Baird--Danielo and Lott: nongradient homogeneous expanding Ricci solitons on…

2006-06-30abs ↗pdf ↗

New model stabilizes asynchronous LTI systems, independent of synchronous stability.

problem Stability of asynchronous LTI systems under randomization and asynchrony.
method Introduced a new model for random asynchronous LTI systems and developed a method for system identification.
result Stability of random asynchronous LTI systems is independent of synchronous stability.

We prove the linear stability of slowly rotating Kerr black holes as solutions of the Einstein vacuum equation: linearized perturbations of a Kerr metric decay at an inverse polynomial rate to a linearized Kerr metric plus a pure gauge term. We work in a natural wave map/DeTurck gauge and show that the pure gauge term …

2019-06-03abs ↗pdf ↗

We study the linear stability of Einstein metrics of Riemannian submersion type. First, we derive a general instability condition for such Einstein metrics and provide some applications. Then we study instability arising from Riemannian product structures on the base. As an application, we estimate the coindex of the E…

2018-08-16abs ↗pdf ↗

Paper improves TD learning algorithm bounds with linear approx.

problem Sharp bounds for TD method performance in MDPs.
method Polyak-Ruppert averaging, universal step size, refined error bounds, stability of random matrices.
result Near-optimal variance and bias terms achieved.

The paper improves stability estimates for soap bubble theorem in curved domains.

problem Stability estimates for the Soap Bubble Theorem in curved domains.
method Leveraging Gagliardo-Nirenberg-type interpolation inequalities.
result Optimal stability estimates for LrL^r deviations of mean curvature from being constant.

In previous work, the authors studied the linear stability of algebraic Ricci solitons on simply connected solvable Lie groups (solvsolitons), which are stationary solutions of a certain normalization of Ricci flow. Many examples were shown to be linearly stable, leading to the conjecture that all solvsolitons are line…

2014-09-10abs ↗pdf ↗

We analyze why some models resist unlearning using linear stability theory.

problem Understanding and predicting when machine learning models resist unlearning.
method Linear stability theory applied to machine learning models, focusing on data coherence and optimization dynamics.
result Data coherence and signal-to-noise ratio (SNR) influence unlearning resistance; lower SNR makes unlearning easier.

The paper proves stability of certain cosmological models with negative spatial curvature.

problem Stability of Friedmann-Lemaître-Robertson-Walker cosmological models with negative spatial curvature.
method Linear stability analysis using Hodge decomposition and energy estimates.
result Uniform boundedness and decay of solutions to the linearized Einstein-Euler system.