Applied Math · Mathematics & Statistics
Optimization & Control
The newest papers in Optimization & Control that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
754 papers, from 31 August 2026 to 5 November 2026: 698 arXiv preprints and 56 OpenAlex records.
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Newest papers, page 4
IncVNM: An Interactive Recommender System with Incremental von Neumann-Morgenstern Utility Learning
In modern recommender systems, users are often presented with products whose outcomes are random.OC-OPD: Observation-coordinated Supervision for On-Policy Distillation
Reverse and forward Kullback--Leibler (KL) divergences provide complementary supervision in on-policy distillation: reverse KL refines the student's active token rankings, and forward KL allocates…Rare Event Constrained Reinforcement Learning with Large Deviations
We study finite-horizon reinforcement learning with a safety constraint on the probability of reaching a failure set.Overcoming Demand Censoring through Randomization for Risk-Sensitive Newsvendor Learning
We study online newsvendor learning with bounded demand, censored observations, and convex nonlinear shortage costs.Non-asymptotic analysis of SGLD with discontinuous stochastic gradients: a new route to portfolio CVaR minimization
Conditional-Value-at-Risk (CVaR) optimization is a fundamental tool in portfolio selection, yet its nonsmooth loss structure poses a challenge for the existing theory of stochastic gradient methods…Conic Certification of Transformer Attention
Attention is the computational core of large language models, yet the verifiers that bound how far an attention head's output can move under input perturbations give no guarantee on how loose their…Log-Driven Semantic Tuning for Mixed Integer Programming Solvers
Automated configuration of mixed-integer programming (MIP) solvers largely relies on black-box optimization.ALDER: A Single-Loop Augmented-Lagrangian Damped Extragradient Method for Nonconvex--Concave Minimax Problems with Nonlinear Coupled Constraints
ALDER, a single-loop augmented-Lagrangian damped extragradient method, is proposed for smooth nonconvex--concave minimax problems with nonlinear coupled inequality constraints.Unbiased Low-Rank Approximation for Repeated Matrix-Vector Multiplication: Stability and Optimal Sampling
Replacing the matrix in an iteration with random low-rank matrices can reduce the cost of matrix-vector multiplication.Agent4FreeFem: A Verification-Guided Framework for Autonomous Topology Optimization
Topology optimization has become an indispensable design tool in the aerospace, automotive, and mechanical engineering industries.Consumption and Investment with Multiple Job-Switching Opportunities
We study finite-horizon optimal switching with affine rewards in a consumption-investment model with finitely many occupational regimes.Entropy-Regularized Reinforcement Learning for the Regime-Switching Consumption-Investment Problem
This paper establishes an entropy-regularized reinforcement learning (ERRL) framework for the continuous-time consumption-investment problem under a regime-switching market model with general…Lower Bounds on Inference Complexity for Polyak-Ruppert Averaged Stochastic Gradient Descent
In this paper, we establish sharp lower bounds for Gaussian approximation of Polyak-Ruppert averaged stochastic gradient descent with polynomially decreasing step sizes.Adaptive Optimizers Can Get a Policy Ranking Wrong: Momentum, Dependent Data, and a Two-Run Remedy
Operators choosing among decision rules, such as when a battery charges or where an idle taxi goes, rank them by estimated long-run value.How Much Can Approximate Equilibria Change the Social Cost of Selfish Routing?
We study approximate Nash equilibria in nonatomic congestion games, with the goal of understanding how much the social cost can change when the equilibrium condition is relaxed.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.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.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.