Applied Math · Mathematics & Statistics
Optimization & Control
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754 papers, from 31 August 2026 to 5 November 2026: 698 arXiv preprints and 56 OpenAlex records.
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Newest papers, page 31
A Convergence Framework for Deep $V$-Learning: Error Propagation and Sharp Action-Gap Bounds
We establish convergence bounds for deep $V$-learning with horizon $H$.Learning Lyapunov Operators for Nonlinear Systems
Constructing Lyapunov functions for nonlinear dynamical systems is a central problem in stability analysis, yet remains challenging.ElastiQP: An Always-Feasible QP Solver for Constrained Robot Control
As robot capabilities increase, quadratic programming (QP)-based controllers must account for a similarly increasing number of constraints to ensure safe, reliable operation.Feasibility and Singularity in High-Order Safety-Critical Control for Quadrotor UAVs
We study high-order safety-critical control of quadrotor teams under bounded inputs and pairwise collision-avoidance constraints.Learning and Control Beyond Linearity: Towards a Non-asymptotic Theory for Bilinear Systems
This tutorial provides a unified view of the emerging area of bilinear learning and control.Learning Choice Model Trees for Feature-Based Multi-Product Pricing: Exact Optimization and Field Evidence
Feature-based multi-product pricing uses customer characteristics to identify demand heterogeneity and tailor prices across products.Optimization over covariance matrices with a parameterized metric
The choice of Riemannian metric can strongly influence the convergence of gradient-based optimization over covariance matrices.Intervention problems in the Linear Threshold Model: A general formulation and new results
We study an optimal intervention problem for linear threshold models.Same Flow, Different Paths: Variance Reduction in Flow Matching
In flow matching (FM), a velocity model $v_θ$ is trained using a predefined path $g_t$ that connects data and noise samples (e.g., $g_t(x_0, x_1) = (1 - t) x_0 + t x_1$).PrecPack: An Efficient Open-Source Exact Solver for Bin Packing with Generalized Precedence Constraints
Efficient resource use in packing and assembly-line applications requires decisions that jointly account for capacity and precedence constraints.Reduced-Space Multi-Fidelity Bayesian Optimization of Process Simulation Models
Optimizing industrial process flowsheets is often computationally prohibitive due to the high cost of rigorous simulations and the curse of dimensionality inherent in complex design spaces.Bridging the Gap Between Homogeneous and Heterogeneous Asynchronous Optimization Is Surprisingly Difficult
Modern large-scale machine learning tasks often require multiple workers, devices, CPUs, or GPUs to compute stochastic gradients in parallel and asynchronously to train model weights.Fenchel-Young Duality Gaps: Certified Early Stopping for Regularized Inverse Problems
We study computable error bounds and certified early stopping for regularized inverse problems, where a data-fidelity term is traded against a regularizer.A tight 1/3-approximation algorithm and fully polynomial-time approximation schemes for the Colored Knapsack Problem
The $\textit{Colored Knapsack Problem}$ (ColKP) generalizes the classical Knapsack Problem by partitioning the items into color classes and requiring the selected items to admit an ordering in which…Derivative-Free Structured Updates for Muon
Muon updates matrix-valued neural-network parameters by orthogonalizing a gradient-based momentum matrix.Random tilts to find stationary points in stochastic convex optimization
We consider the problem of finding stationary points of stochastic convex functions and related variational inequalities.An explicit solution of the five-expert prediction PDE and the exact optimality set of COMB
In this paper, we derive an explicit solution of the stationary prediction with expert advice PDE for five experts.Steady-State Convergence of Stochastic Approximation
For constant-stepsize stochastic approximation (SA), the iterates converge in distribution to a stationary law that depends on the stepsize $α.$ Steady-state convergence (SSC) concerns the limit of…Distributed Fast Fixed-Point Algorithms for Composite Monotone Inclusions over Networks
This paper aims to develop new and efficient distributed algorithms for solving a class of monotone inclusions, $0 \in \sum_{i=1}^n (G_ix + T_ix)$, over a connected network of $n$ agents, where the…High-Probability Nash Regret for Decentralized Learning in Markov $α$-Potential Games: Episodic and Fully Online Asynchronous Algorithms with Applications to Markov Congestion Games
We study decentralized learning of Nash equilibria (NE) in infinite-horizon discounted Markov games under bandit feedback, focusing on Markov $α$-potential games.