Research
On-device research index

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.

168,695 papers · 148 categories

Trend · papers per month

117234350467 · Jun 202019922001200920172026
48 results for fixed-point analysis

A new clustering framework using fixed points for data analysis.

problem Lack of unified understanding and application of clustering algorithms in data analysis.
method Restated model-based clustering using fixed point theory, iteratively constructing contraction maps to find cluster centers.
result Unified clustering framework reveals convergence mechanisms and interconnections among clustering algorithms.

Two possible definitions of fixed points in the self-similar analysis of time series are considered. One definition is based on the minimal-difference condition and another, on a simple averaging. From studying stock market time series, one may conclude that these two definitions are practically equivalent. A forecast …

1998-03-05abs ↗pdf ↗

A recent analysis of a model of iterative neural network in Hilbert spaces established fundamental properties of such networks, such as existence of the fixed points sets, convergence analysis, and Lipschitz continuity. Building on these results, we show that under a single mild condition on the weights of the network,…

2019-08-16abs ↗pdf ↗

Fixed points of nonnegative neural networks are analyzed using fixed point theory.

problem Analyzing fixed points in nonnegative neural networks.
method Fixed point theory, nonlinear Perron-Frobenius theory, monotonic and scalable mappings.
result Conditions for the existence of fixed points in nonnegative neural networks are provided.

The Bass model is calibrated to vanilla options using a fixed-point equation.

problem Calibration of the Bass local volatility model to vanilla options.
method Solving a fixed-point equation to achieve calibration.
result Existence and uniqueness of the solution to the fixed-point equation, and linear convergence of the fixed-point iteration scheme.

Interpreting gradient methods as fixed-point iterations, we provide a detailed analysis of those methods for minimizing convex objective functions. Due to their conceptual and algorithmic simplicity, gradient methods are widely used in machine learning for massive data sets (big data). In particular, stochastic gradien…

2017-06-29abs ↗pdf ↗

New methods for federated learning reduce communication costs.

problem Efficiently solving optimization problems in a distributed setting.
method Developed two strategies for achieving consensus in federated learning: fixed number of local steps and randomized computations.
result Convergence analysis and experiments show benefits of the proposed methods.

The paper studies how neural networks evolve representations, finding a unique fixed point for nonlinear activations.

problem Understanding how neural networks transform input data across layers.
method Theoretical framework for the evolution of the kernel sequence, using mean-field regime and Hermite polynomials.
result For nonlinear activations, the kernel sequence converges globally to a unique fixed point.

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.

Banach's fixed point theorem for contraction maps has been widely used to analyze the convergence of iterative methods in non-convex problems. It is a common experience, however, that iterative maps fail to be globally contracting under the natural metric in their domain, making the applicability of Banach's theorem li…

2017-02-23abs ↗pdf ↗

Minimum numbers of fixed points or of coincidence components (realized by maps in given homotopy classes) are the principal objects of study in topological fixed point and coincidence theory. In this paper we investigate fiberwise analoga and represent a general approach e.g. to the question when two maps can be deform…

2010-02-09abs ↗pdf ↗

The mathematical model proposed by George Soros for his theory of reflexivity is analyzed under the framework of discrete dynamical systems. We show the importance of the notion of fixed points for explaining the behavior of a reflexive system governed by its cognitive and manipulative functions. The interrelationship …

2009-01-28abs ↗pdf ↗

Study finite group actions on symplectic Calabi-Yau 4-manifolds with non-zero first Betti number.

problem Determine fixed-point set structure of symplectic Calabi-Yau 4-manifolds with certain group actions.
method Analysis of symplectic surfaces and disjoint embeddings in rational 4-manifolds.
result Symplectic Calabi-Yau 4-manifolds are shown to be T2T^2-bundles under specific group actions.

Improved convergence speed of principal component analysis through modified learning rules.

problem Slow convergence for covariance matrices with close eigenvalues.
method Introduced an additional term to the objective function to mitigate convergence issues.
result Significantly improved convergence speed confirmed through simulations.

Study compares methods for computing hypergradients in machine learning problems.

problem Computing exact hypergradients in machine learning is difficult.
method Investigates reverse mode iterative differentiation and approximate implicit differentiation methods.
result Unified analysis provides iteration complexity bounds and hierarchy of methods.

Paper generalizes Hardy-Rogers maps for market equilibrium analysis in duopoly markets.

problem Existence and uniqueness of market equilibrium in duopoly markets with non-differentiable, nonlinear response functions.
method Coupled fixed points approach for generalized Hardy-Rogers maps.
result Enriched understanding of market equilibrium in duopoly markets with non-differentiable response functions.

The paper classifies circle actions on 6D manifolds with isolated fixed points.

problem Classifying circle actions on 6D manifolds with isolated fixed points.
method Performing equivariant connected sums at fixed points with specific manifolds.
result A sequence of operations can reduce the fixed point data to the empty collection.

Recent proofs of classical theorems in polynomial algebra and functional analysis are discussed, which use tools from the topology of real manifolds. Simpler proofs were discovered in the new century, of the Hilbert Nullstellensatz, and the Gelfand-Mazur Theorem. We give a related proof that an irreducible real polynom…

2015-02-01abs ↗pdf ↗

Study null hypersurfaces with privileged vector fields, extending surface gravity and defining new horizon types.

problem Characterize null hypersurfaces with privileged vector fields and extend surface gravity.
method Derive identities relating deformation tensor to intrinsic and extrinsic geometry, introduce generalized surface gravity, analyze Lie derivatives, and define new horizon types.
result Introduce three new horizon types that generalize existing concepts to arbitrary topologies and fixed points.

REMAL: Residual Equilibrium Manifold Active Learning for Surrogate-Based Multidisciplinary Design Analysis

problem Multidisciplinary design analysis of coupled engineering systems requires solving equilibrium states where all disciplinary coupling variables are consistent.
method Residual manifold surrogate modeling framework for coupled systems.
result REMAL learns a surrogate model of the joint residual manifold via multitask Gaussian process models.

The study analyzes sharpness dynamics in neural networks, revealing mechanisms and conditions.

problem Understanding sharpness in neural network training.
method Fixed point analysis and edge of stability analysis in a simplified 2-layer linear network.
result Reveals mechanisms behind sharpness trends, conditions for edge of stability, and a period-doubling route to chaos.

Quantized neural networks can represent all fixed-point functions under certain conditions.

problem Expressive power of quantized neural networks under fixed-point arithmetic.
method Analyzing necessary and sufficient conditions for quantized networks to represent all fixed-point functions.
result Various popular activation functions satisfy the sufficient condition for representing all fixed-point functions.

Study circle actions on unitary manifolds with discrete fixed points.

problem Understanding circle actions on compact unitary manifolds with discrete fixed points.
method Prove relationships between weights at fixed points and derive results regarding the first equivariant Chern class and Hirzebruch χyχ_y-genus.
result Derive a multigraph encoding fixed point data, leading to new insights into unitary S1S^1-manifolds.

Research shows quadratic growth in derivative maxima for certain interval diffeos with parabolic fixed points.

problem Analyzing the growth of derivative maxima for C2C^2 interval diffeomorphisms with parabolic fixed points.
method Examining C2C^2 diffeomorphisms with only parabolic fixed points, focusing on tangency and repelling behavior.
result Maximal growth of derivative maxima is exactly quadratic for diffeomorphisms with a non-quadratic tangency to identity at a repelling fixed point.

New proof for 6D symplectic manifold with 4 fixed points.

problem Classifying the integral cohomology ring and total Chern class for 6D symplectic manifolds with 4 fixed points.
method New different argument using moment map values and weights of fixed points.
result Determined the sets of weights and global invariants for the manifold.

The paper introduces two new metrics on outer space and shows fixed points for their actions.

problem Analyzing metrics on outer space and their geometric group theory implications.
method Defined and analyzed entropy and pressure metrics on outer space, comparing to Weil-Petersson metric.
result For rank r4r \geq 4, the metrics have fixed points in their actions on outer space.

Improved convergence of fixed-point methods using windowed Anderson acceleration.

problem Improving convergence of fixed-point methods for symmetric operators.
method Windowed Anderson acceleration for symmetric fixed-point iterations.
result Windowed Anderson acceleration improves convergence over standard fixed-point methods.

A fixed point theorem is proved for inverse transducers, leading to an automata-theoretic proof of the fixed point subgroup of an endomorphism of a finitely generated virtually free group being finitely generated. If the endomorphism is uniformly continuous for the hyperbolic metric, it is proved that the set of regula…

2012-03-07abs ↗pdf ↗

Paper finds at least 6 fixed points for a specific circle action on a 10D manifold.

problem Finding the minimum number of fixed points for a circle action on a 10D almost complex manifold.
method Established a lower bound by showing the non-existence of a circle action with 4 fixed points.
result There are at least 6 fixed points for a circle action on a 10D compact almost complex manifold.

Let GG be a compact Lie group acting isometrically on a compact Riemannian manifold MM with nonempty fixed point set MGM^G. We say that MM is fixed-point homogeneous if GG acts transitively on a normal sphere to some component of MGM^G. Fixed-point homogeneous manifolds with positive sectional curvature have been c…

2009-11-06abs ↗pdf ↗

Incorrect fixed point assertions in digital topology are discussed.

problem Incorrect, incorrectly proven, or trivial fixed point assertions in digital topology.
method Continues earlier work on identifying and critiquing bad fixed point assertions.
result Clarifies the nature and extent of incorrect fixed point assertions in digital topology.