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 18
Curating Always-Loaded Context for LLM Agents: A Capacitated Assortment Model with Censored Feedback
At the start of every session, LLM agents load a fixed context file, such as $\texttt{AGENTS.md}$.Preserving Unstable Modes Through Inverse Dynamics in JEPA World Models
Robotic systems often exhibit unstable modes, along which small perturbations and disturbances can cause unbounded growth unless corrected through feedback.A Neural JKO Scheme for Hellinger-Kantorovich Gradient Flows via Monge-Growth Pairs
We develop a mesh-free neural JKO scheme for advection-reaction-diffusion equations with a gradient-flow structure in the Hellinger-Kantorovich (HK) geometry of unbalanced optimal transport.Belief-Informed Hybrid Control with Almost-Sure Target-Set Convergence
Controlling a hybrid system to a target set under parameter uncertainty can require informative actions that temporarily drive the system state away from the specified set.Scen-Opt: A Scenario Optimization Toolbox for Data-Driven Convex Programming
The scenario approach is a well-established statistical framework for data-driven decision-making.Network Intervention by Polling Strategic Agents
A planner in a network of strategic agents faces three entangled challenges: the optimum depends on agents' private information, queried agents may misreport to steer the outcome, and exact…CNet: A Complex-Valued Deep Learning Framework with Wirtinger Autodifferentiation and FFT--Hadamard Convolution
CNet is a C++/CUDA framework for building deep complex-valued neural networks (CVNNs) and optimizing complex functions by gradient descent with Wirtinger derivatives.Rapid Fredholm stabilization of the Kuramoto--Sivashinsky equation with unrestricted, spatially-varying anti-diffusion
We develop the first feedback design for rapid stabilization of the Kuramoto--Sivashinsky equation with a spatially varying anti-diffusion coefficient.Trust-Region Optimization for Smooth Potential-Interaction Energies in Wasserstein Space
Finding low-energy configurations of interacting particles and approximating probability distributions lead to the minimization of potential-interaction energies in Wasserstein space.LASER: Latent Space Adjoint Matching for Support-Constrained Entropy-Regularized Offline RL
While offline reinforcement learning (RL) enables policy optimization from static datasets without costly online interaction, it remains bottlenecked by the risk of executing out-of-distribution…FedRSPO+: A Heterogeneity-aware Algorithm for Decision-focused Federated Learning
Decision-focused learning (DFL) trains predictive models for downstream optimization, but existing methods largely assume centralized data.Dijkstra Is NOT Greedy: A Global-to-Local Proof of Correctness
Dijkstra's algorithm is almost universally classified as a canonical greedy algorithm.Dimension-Free Decentralized Nonsmooth Nonconvex Stochastic Optimization
We investigate decentralized nonsmooth nonconvex stochastic optimization over a network of $n$ nodes, with the goal of finding an $(δ,ε)$-Goldstein stationary point.Large Stepsizes Federated Learning on Logistic Regression with Linearly Separable Data: The Case of Heterogeneous Devices
This paper revisits the distributed learning problem for training a multinomial logistic regression model with the Federated Averaging ($\texttt{FedAvg}$) algorithm.Structural Foundations of Nonlinear Systems with Unknown Inputs: The UID-Induced Normal Form and Minimal-Sensing Structure-from-Motion
This paper establishes the first general structural solution to the problem of state estimation for nonlinear systems driven by unknown inputs.Last-Iterate Convergence Rate of Normalized Gradient Descent under Hölder Smoothness
Normalized gradient descent is a widely studied adaptive optimization method.Ramp Metering Control via Hybrid State Deep Reinforcement Learning in Partially Observable Connected Vehicle Environments
Freeway on-ramp merges are major sources of congestion, causing significant economic and environmental costs.A posteriori error bounds for the Uncertain Volatility Model
We develop a posteriori primal-dual bounds for numerical approximations of European option prices in the Uncertain Volatility Model.Retirement Planning with Minimum Guarantees for Both Beneficiaries and Fund Managers
This article studies a retirement planning problem from a new perspective in which a retiree delegates an initial lump sum to a professional fund manager.On the Cardinality of Optimal Representations in the Binary-Source Information Bottleneck
The information bottleneck (IB) seeks a representation $U$ of a source $X$ that retains as much information as possible about a target $Y$, subject to a constraint on $I(U;X)$.