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Mathematics & Statistics
New mathematics and statistics is posted on arXiv, often long before it appears in a journal. This page shows the newest papers ReadSearch has read, from algebra and geometry to analysis, probability and applied mathematics.
The newest 1,000 papers, from 13 October 2026 to 5 November 2026: 971 arXiv preprints and 29 OpenAlex records.
Newest papers, page 16
Convergence of non-symmetric forms with changing reference measures
We develop a functional-analytic theory of convergence for non-symmetric generalized Dirichlet forms defined on a sequence of Hilbert spaces $H_n$ converging to a limit space $H$ in the sense of…Local Budget Benefits, Population Commitment, and Solver Performance: A DGO Case Study with Controlled DE Transfer
An evaluated candidate can improve a local search step, alter the population used by later steps, and affect a solver's final result.Quantum Vehicle Routing Problem: a smart initialization strategy for ill-conditioned optimization landscapes
With the expansion of complex transport infrastructure, new paths for linking different destinations have emerged, allowing the definition of multiple routes.Traveling Salesman Problem on Graphs with Proportional Independent Set
We give a deterministic algorithm for minimum-cost Hamiltonian cycle in undirected graphs with arbitrary real edge costs and an independent set of size at least $αn$, for any fixed $3/7<α\le1/2$.General Frequency Principle for Linear Approximation Classes
In this paper, we study a general frequency principle under gradient descent training for the finite linear approximation classes.Longitudinal electric corner modes in continuum quantum gauge theory with matter
Subregions in gauge theories give rise to edge modes and corner charges supported on their boundaries.Generative SDEs with Trainable Diffusion and Density-Based Losses
We develop a divergence-kernel method for jointly optimizing neural SDE drift and diffusion fields and the initial Gaussian distribution, using losses that depend directly on the terminal density.Stochastic Mirror Descent under Dependent Observations
We study the non-asymptotic convergence of Stochastic Mirror Descent (SMD) algorithm when the noisy first-order oracle is driven by dependent observations.Instrumental Transfer Learning for Solution Operators
Data-driven learning for the solution operator of a differential equation has broad scientific importance, but observations from a target system are often scarce and costly to collect.Feature-preserving interface reconstruction using piecewise circles and cusps
We present a geometric interface reconstruction method for Volume-of-Fluid (VOF) simulations that captures both curved interfaces and sharp features using only volume fraction data.Sparse descent subspace-Newton thresholding algorithm for sparse optimization problems
In this paper, we propose a sparse descent direction derived from the Newton direction within a low-dimensional subspace for sparse optimization problems.Riemannian Optimization on Unknown Manifolds via Stochastic Proximal Refinement
We study Riemannian optimization on an unknown manifold accessed only through feasible samples.Physically Constrained Kinematic Calibration for High-Precision Robotic Needle Guidance
Percutaneous needle insertion is a common practice in minimally invasive procedures whose clinical success depends on accurate needle placement.Improving the Optimization Landscape of Matrix Completion with $ε$-close Surrogates
Non-convex optimization is central to machine learning and AI, yet unlike its convex counterpart, it still lacks a general and principled framework.Improved Approximation Guarantees for Periodic-Review Stochastic Inventory Control
In periodic-review stochastic inventory control, replenishment policies must balance holding and backlogging costs while responding to uncertain demands and evolving forecasts that may be…Distributed Grid Search for Hyperparameter Tuning
The performance of many distributed optimization algorithms over peer-to-peer networks strongly depends on the choice of their hyperparameters.AMPERe: an exactly divergence-free quadrature-by-expansion evaluator for near-surface Biot--Savart and virtual-casing fields in fusion geometries
Accurate magnetic-field evaluation on and near current-carrying surfaces is a recurring computational bottleneck in magnetic-confinement fusion.On $t$-designs supported by self-orthogonal codes
We study self-orthogonal $t$-$(v,k,λ)$ designs satisfying the condition that the codes generated by the designs are self-orthogonal codes whose codewords of minimum weight $k$ correspond to the…A complete analytical characterization of optimal collision-free motion for two robots
Collision-free motion planning for multi-agent robotic systems remains an active research area because of the complexity of coordinating robot trajectories, with applications ranging from…Reliability-Weighted Direct Preference Optimization: Penalized Weights for Robust Preference Learning
Direct Preference Optimization (DPO) treats every reported comparison as correct, yet preference data contain reversed, tied or otherwise noisy comparisons.
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