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Showing 15713 results for "machine learning" in Mathematics
Mathematics Preprint PDF DOI

Data-Driven Continuous-Time Linear Quadratic Regulator via Closed-Loop and Reinforcement Learning Parameterizations

Armin Gie{ss}ler, Felix Thommes, Soren Hohmann ยท 2026

This paper studies data-driven approaches to the continuous-time linear quadratic regulator (LQR) problem based on two existing parameterizations, namely a closed-loop (CL) parameterization from behavโ€ฆ

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Mathematics Preprint PDF DOI

On the Extremal Energy of Complex Unit Gain Dumbbell Graphs

Silin Huang ยท 2026

We study the extremal energy problem for complex unit gain graphs whose underlying graph is the dumbbell graph $D_{r,s,\ell}$. An explicit expression of its characteristic polynomial is derived in terโ€ฆ

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Mathematics Preprint PDF DOI

Rising GUE Eigenvalue Process from a Fixed Level

Zoe Himwich ยท 2026

We construct the multilevel correlation kernel for the rising GUE eigenvalue process starting from a fixed initial configuration $x^{(m)}$, and show that it converges on short time scales (as quickly โ€ฆ

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Mathematics Preprint PDF DOI

A Systematic Review of Recent Advancements in PINN Augmented Deep Learning and Mathematical Modeling for Efficient Portfolio Management

Bahadur Yadav, Sanjay Kumar Mohanty ยท 2026

In finance, portfolio management is a traditional yet difficult problem that has drawn attention from practitioners and researchers for many years. However, there are still difficult technological proโ€ฆ

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Mathematics Preprint PDF DOI

Quantitative homogenization of the maximal action of curves in a Brownian potential

Felix Otto, Matteo Palmieri ยท 2026

Motivated by an optimal-matching problem (Leighton-Shor) and the random-field Ising model (Aizenman-Wehr, Ding-Wirth), we consider a variational problem for graphs in $1+1$ dimension maximizing an actโ€ฆ

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Mathematics Preprint PDF DOI

The Bernstein-von Mises theorem for Bayesian one-pass online learning

Jeyong Lee, Junhyeok Choi, Dongguen Kim, Minwoo Chae ยท 2026

Bayesian online learning provides a coherent framework for sequential inference. However, its theoretical understanding remains limited, particularly in the one-pass setting. Existing theoretical guarโ€ฆ

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Mathematics Preprint PDF DOI

A Regularized Hessian-Free Inexact Newton-Type Method with Global $\mathcal{O}(k^{-2})$ Convergence

Leandro Farias Maia, Antonio Victor B. Nascimento, Paulo Sergio M. Santos, Gilson N. Silva ยท 2026

We propose a regularized Hessian-free Newton-type method for minimizing smooth convex functions with Lipschitz continuous Hessians. The algorithm constructs an approximate Hessian by finite differenceโ€ฆ

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Mathematics Preprint PDF DOI

Mean-Field Systems with Heterogeneous Subteams: Optimality of Cluster-Symmetric Independent Policies and Equivalence with Decentralized McKean-Vlasov Control of Cluster-Representative Agents

Connor S. Braun, Sina Sanjari, Naci Saldi, Gunnar Blohm, Serdar Yuksel ยท 2026

Across science and engineering, mean-field methods have been a powerful and versatile approach for the analysis of systems of many interacting elements. However, common arguments used to characterize โ€ฆ

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Mathematics Preprint PDF DOI

Continuous-time q-learning for mean-field control with common noise, part-II: q-learning algorithms

Zhenjie Ren, Xiaoli Wei, Xiang Yu, Xun Yu Zhou ยท 2026

This paper is a continuation work of Ren et al. (2026) aiming to further devise q-learning algorithms for mean-field control (MFC) with controlled common noise. Based on the relaxed control formulatioโ€ฆ

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Mathematics Preprint PDF DOI

Continuous-time q-learning for mean-field control with common noise, part-I: Theoretical foundations

Zhenjie Ren, Xiaoli Wei, Xiang Yu, Xun Yu Zhou ยท 2026

This paper investigates the continuous-time counterpart of the Q-function for entropy-regularized mean-field control (MFC) with controlled common noise, coined as q-function by Jia and Zhou (2023) in โ€ฆ

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Mathematics Preprint PDF DOI

Hamilton decompositions of the directed 5-torus for odd modulus

SangHyun Park ยท 2026

We prove that the directed five-dimensional torus $D_5(m) = \operatorname{Cay}((\mathbb{Z}_m)^5, \{e_0, e_1, e_2, e_3, e_4\})$ has a Hamilton decomposition for every odd integer $m \geq 3$. This is thโ€ฆ

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Mathematics Preprint PDF DOI

Man, Machine, and Mathematics

Akshunna S. Dogra ยท 2026

Nonlinear models and optimization methods have successfully tackled a rapidly growing set of problems in recent years. Indeed, a relatively small toolbox of such models and methods can provide sufficiโ€ฆ

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Mathematics Preprint PDF DOI

Learning Over-Relaxation Policies for ADMM with Convergence Guarantees

Junan Lin, Paul J. Goulart, Luca Furieri ยท 2026

The Alternating Direction Method of Multipliers (ADMM) is a widely used method for structured convex optimization, and its practical performance depends strongly on the choice of penalty and relaxatioโ€ฆ

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Mathematics Preprint PDF DOI

Approximating the Network Design Problem for Potential-Based Flows

Max Klimm, Marc E. Pfetsch, Martin Skutella, Lea Strubberg ยท 2026

We develop efficient algorithms for a fundamental network design problem arising in potential-based flow models, which are central to many energy transport networks (e.g., hydrogen and electricity). Iโ€ฆ

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Mathematics Preprint PDF DOI

Function-free Optimization via Comparison Oracles

Katya Scheinberg, Zikai Xiong ยท 2026

In this work, we study optimization specified only through a comparison oracle: given two points, it reports which one is preferred. We call it function-free optimization because we do not assume acceโ€ฆ

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Mathematics Preprint PDF DOI

Beyond Linear Additive and Hill Functions: A General Logistic Reformulation of Delay-Coupled Gene Regulatory Networks with Equilibrium Analysis, Hopf Bifurcation, and Lipschitz Stability

Ismail Belgacem ยท 2026

Hill functions, dominant in gene regulatory network modeling, carry fundamental limitations: at non-integer cooperativity exponents, routine when fitting dose-response data, derivatives diverge at theโ€ฆ

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Mathematics Preprint PDF DOI

Induced Stackelberg Equilibrium Seeking via Iterative Tikhonov Regularization

Silvia Cianchi, Anibal Sanjab, Sergio Grammatico ยท 2026

Existing methods for learning Stackelberg equilibria typically assume that the followers' (variational, generalized) Nash equilibrium is unique. However, in the presence of multiple equilibria, withouโ€ฆ

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Mathematics Preprint PDF DOI

Quasar-Convex Optimization: Fundamental Properties and High-Order Proximal-Point Methods

Masoud Ahookhosh, Jose M.M. de Brito, Alireza Kabgani, Felipe Lara, Jinyun Yuan ยท 2026

We study the optimization of (strongly) quasar-convex functions, a class that arises naturally in many machine learning and data science applications due to its favorable properties. The fundamental pโ€ฆ

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Mathematics Preprint PDF DOI

Reinforcement Learning for Public Safety Power Shutoffs Under Decision-Dependent Uncertainty and Nonlinear Wildfire Ignition Models

Prasanna Raut, Chaoyue Zhao, Alexandre Moreira ยท 2026

Power grid infrastructure is an increasingly significant source of wildfire ignitions and poses severe risks to communities in fire-prone regions. Public Safety Power Shutoffs (PSPS) have emerged as aโ€ฆ

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Mathematics Preprint PDF DOI

Symmetric Limit Cycles in 3D Piecewise Linear Systems with Visible-visible Two-Fold Singularity

Samuel Carlos S. Ferreira, Bruno R. Freitas, Joao Carlos R. Medrado ยท 2026

We analyze a three-dimensional discontinuous piecewise linear system \(Z=(X,Y)\) whose switching manifold \(\Sigma\) contains visible-visible two-fold intersection lines. Assuming that the matrices \(โ€ฆ

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