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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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2815628431,124 · Jun 202019922001200920172026
48 results for finite set systems

The paper sets sample complexity bounds for identifying LTI systems from a finite set.

problem Identifying an LTI system from a finite set of possible systems using trajectory data.
method Maximum likelihood estimator and information theory tools.
result Upper and lower bounds for sample complexity are derived, independent of stability assumption.

Study on self-similar sets on Riemannian manifolds with new separation conditions.

problem Analyzing self-similar sets on Riemannian manifolds with new separation conditions.
method Formulated weak separation and finite type conditions for conformal iterated function systems on Riemannian manifolds.
result Obtained formulas for Hausdorff dimensions of self-similar and graph self-similar sets.

Study shows finiteness of magnetic hypersurfaces on closed manifolds.

problem Understanding the finiteness of magnetic hypersurfaces on closed manifolds.
method Introduced a dynamical version of the second fundamental form to generalize a previous result.
result Real-analytic negatively ss-curved magnetic systems on closed real-analytic manifolds have only finitely many closed totally ss-magnetic hypersurfaces.

The study describes metrics geodesically compatible with Nijenhuis operators and their applications to integrable systems.

problem Geodesically compatible metrics and their applications to integrable systems.
method Describes metrics geodesically compatible with a gl-regular Nijenhuis operator and shows how these metrics relate to integrable PDE systems.
result Every metric geodesically compatible with a Nijenhuis operator gives a finite-dimensional reduction of an integrable PDE system.

Deep neural networks with memory learn reduced equations from partial data.

problem Constructing governing equations for unknown dynamical systems from limited data.
method Formulate a discrete approximation of memory integrals, use deep neural networks to incorporate history terms.
result Deep neural networks can learn reduced equations with memory from partial data.

Stabilization of linear systems with unknown dynamics is a canonical problem in adaptive control. Since the lack of knowledge of system parameters can cause it to become destabilized, an adaptive stabilization procedure is needed prior to regulation. Therefore, the adaptive stabilization needs to be completed in finite…

2018-07-22abs ↗pdf ↗

The paper analyzes deep neural networks using control theory to set a time limit for their convergence.

problem Understanding the finite-time convergence of deep neural networks.
method Lyapunov based analysis of the loss function, control theory framework, finite-time control of non-linear systems.
result A priori guarantees of finite-time convergence for deep neural networks are provided.

Autostackability for finitely generated groups is defined via a topological property of the associated Cayley graph which can be encoded in a finite state automaton. Autostackable groups have solvable word problem and an effective inductive procedure for constructing van Kampen diagrams with respect to a canonical fini…

2013-07-18abs ↗pdf ↗

New scalable MARL framework for dynamic networked systems.

problem Scalability in multi-agent reinforcement learning with dynamic dependencies.
method Scalable Actor Critic framework for non-local and stochastic dependencies.
result Finite-time error bound showing convergence rate dependence on information spread speed.

We prove that finite Morse index solutions to the Allen-Cahn equation in R2\R^2 have {\bf finitely many ends} and {\bf linear energy growth}. The main tool is a {\bf curvature decay estimate} on level sets of these finite Morse index solutions, which in turn is reduced to a problem on the uniform second order regularit…

2017-05-18abs ↗pdf ↗

Study connects bank default models using dynamic contagion.

problem Understanding default contagion in heterogeneous interbank systems.
method Proposes a dynamic default contagion model with endogenous early defaults for a finite set of banks, reformulating as a stochastic particle system.
result Existence of clearing systems and continuity of the system response for the mean-field problem.

Unified framework for solving fixed-point equations in deterministic and stochastic settings.

problem Solving fixed-point equations for seminorm-contractive operators in both deterministic and stochastic contexts.
method Fixed-point theorem and stochastic approximation analysis.
result Unified finite-sample bounds for various reinforcement learning algorithms.

We define a new class of racks, called finitely stable racks, which, to some extent, share various flavors with Abelian groups. Characterization of finitely stable Alexander quandles is established. Further, we study twisted rack dynamical systems, construct their cross-products, and introduce representation theory of …

2016-11-14abs ↗pdf ↗

Paper reduces sample complexity for bilinear systems identification to nearly constant.

problem Identifying discrete-time bilinear systems under bounded disturbances.
method Uses trajectory-dependent regressors and polynomial mean-square state growth analysis.
result Proves sample complexity of O~(1/ε)\widetilde{\mathcal O}(1/ε) for estimation error εε.

Let ΛΛ be the limit set of a conformal dynamical system, i.e. a Kleinian group acting on either finite- or infinite-dimensional real Hilbert space, a conformal iterated function system, or a rational function. We give an easily expressible sufficient condition, requiring that the limit set is not too much bigger than …

2015-04-07abs ↗pdf ↗

Constructs initial data for Einstein vacuum equations involving multiple localized gravitational sources.

problem Modeling the interaction of distant gravitational systems in general relativity.
method Time-symmetric initial data construction using gluing schemes and localized sources.
result Produces initial data sets with finite ADM mass and multiple Einstein-Rosen bridges.

Guaranteed reachable set for unknown nonlinear systems on manifolds.

problem Determining reachable set for unknown nonlinear systems on manifolds.
method Underapproximations of reachable set using local dynamics and bounds on dynamics rate of change.
result Guaranteed set of reachable states for systems on complete Riemannian manifolds.

The paper solves integrable systems of PDEs, including famous equations.

problem Constructing solutions for multicomponent integrable PDEs.
method Reduction to a finite-dimensional system, using Nijenhuis geometry.
result Animations of multi-component soliton and cnoidal solutions.

End-to-end algorithm for controlling bilinear systems with probabilistic noise.

problem Controlling bilinear systems with noisy data.
method Proposes an end-to-end algorithm using statistical learning theory and robust controller design.
result Derived finite sample identification error bounds and structurally suitable for control.

Study applies inverse scattering to BKM systems, linking spectra and integrable systems.

problem Applying inverse scattering to BKM systems.
method Developed methods for BKM systems, relating Schrödinger-Hill operators, Neumann system, and KdV equations.
result Initial observations indicate potential for applying inverse scattering to BKM systems.

New bounds for adaptive control in high dimensions without fixed state space.

problem Adaptive control of linear systems in high or infinite dimensions.
method Novel perturbation bound for certainty equivalence, scaling with prediction error.
result First regret bounds for LQR in infinite dimensional systems, independent of ambient dimension.

A new stochastic algorithm approximates optimal distributions without requiring propagation of chaos.

problem Optimizing functionals over probability distributions using finite particle systems.
method Virtual particle stochastic approximation, viewed as a form of stochastic gradient descent in the Wasserstein space.
result The algorithm's output converges to the optimal distribution and produces i.i.d. samples.

In this paper, we show that the boundary Σ(W,S)\partialΣ(W,S) of a right-angled Coxeter system (W,S)(W,S) is minimal if and only if WS~W_{\tilde{S}} is irreducible, where WS~W_{\tilde{S}} is the minimum parabolic subgroup of finite index in WW. We also provide several applications and remarks. In particular, we obtain that for…

2006-06-01abs ↗pdf ↗

Open, connected, saturated sets W without holonomy in codimension one foliations play key roles as fundamental building blocks. Here, for the case of foliated 3-manifolds, we produce a finite system of closed, convex, non-overlapping polyhedral cones in the first cohomology of W with real coefficients such that the iso…

2011-08-03abs ↗pdf ↗

CASP selects reliable policies for two-stage recommender systems by considering both value and support.

problem The selection of a generator in two-stage recommender systems affects both the policy value and the data support used to estimate it.
method CASP combines doubly robust value estimation with a support-burden penalty.
result CASP selects lower-burden policies when estimated value and support credibility are in tension.

Lie systems form a class of systems of first-order ordinary differential equations whose general solutions can be described in terms of certain finite families of particular solutions and a set of constants, by means of a particular type of mapping: the so-called superposition rule. Apart from this fundamental property…

2011-03-21abs ↗pdf ↗

Smooth fractal trees via analytic generators, preserving combinatorial and geometric properties.

problem Constructing smooth fractal trees from discrete models.
method Using analytic generator fields to integrate smooth vector fields in an internal state space, generating geometric curves as projections of generator trajectories.
result Analytic generators can represent any discrete tree specification and preserve the asymptotic limit geometry.

Study stationary measures and orbit closures for non-abelian actions on surfaces.

problem Classify stationary measures and orbit closures for non-abelian action on a surface.
method Use a finite verifiable average growth condition and results from Brown and Rodriguez Hertz.
result Show that under certain conditions, the only nonatomic stationary measure is the given smooth invariant measure, and every orbit closure is either finite or dense.

QENDy learns quadratic dynamics from nonlinear systems data.

problem Identifying governing equations of highly nonlinear dynamical systems.
method QENDy embeds nonlinear dynamics into a quadratic feature space, requiring trajectory data and preselected basis functions.
result QENDy accurately identifies quadratic dynamics and outperforms SINDy and deep learning methods.

In this paper, we analyze the finite sample complexity of stochastic system identification using modern tools from machine learning and statistics. An unknown discrete-time linear system evolves over time under Gaussian noise without external inputs. The objective is to recover the system parameters as well as the Kalm…

2019-03-21abs ↗pdf ↗

The paper studies random dynamical systems of polynomial automorphisms on C^2 and finds mean stability.

problem Random dynamical systems of polynomial automorphisms on C^2.
method Generic random dynamical systems of polynomial automorphisms are shown to have mean stability.
result A generic random dynamical system of polynomial automorphisms on C^2 has mean stability.

Simplified proof of mass center system's uniqueness and generalized Pappus' theorem across Euclidean, spherical, and hyperbolic geometries.

problem Proving the uniqueness of the mass center system in non-Euclidean geometries and deriving a generalized Pappus' theorem.
method Revisiting and simplifying G.A. Galperin's proof, extending the mass center system to manifolds, and deriving a generalized Pappus' theorem.
result Unified and simpler proofs for Pappus' theorem in Euclidean, spherical, and hyperbolic geometries.