#stochastic optimization

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10 papers match

eess.SP2026

A Stochastic Optimization Framework for RIS-Aided Wireless Network Design

Davide Gagliardi, Alessio Zappone, Domenico Ciuonzo +1

The paper proposes a stochastic optimization framework using continuous cross‑entropy and Metropolis‑Hastings methods to design reconfigurable intelligent surface (RIS) configurati…

#reconfigurable intelligent surfaces#stochastic optimization#continuous cross-entropy#metropolis-hastings
math.OC2026

The optimality of an (s, S) hiring policy on a workforce planning problem with fixed recruitment costs and binomial turnover

Zhen Chen, Roberto Rossi, Belen Martin-Barragan +1

The paper analyzes a finite‑horizon workforce planning problem with fixed hiring costs and binomial turnover, proving that the optimal hiring rule follows an (s, S) policy and prov…

#workforce planning#stochastic optimization#inventory control#hiring policies
cs.LG2026

The Convergence Behavior of Adam under Heavy-Tailed Noise

Yijiang Pang

The paper provides the first convergence guarantees for the standard vector-form Adam optimizer under heavy‑tailed stochastic noise, showing convergence to stationary points with s…

#optimization#stochastic optimization#adam optimizer#heavy-tailed noise
cs.LG2026

Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise

Bin Luo, Chengchang Liu, Jonathan Allcock +2

The paper proposes quantum mean estimators for heavy‑tailed random variables and uses them to design quantum stochastic gradient descent methods that achieve lower query complexity…

#quantum algorithms#stochastic optimization#heavy-tailed noise#gradient descent
math.OC2026

A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimization

Wei Liu, Muhammad Khan, Gabriel Mancino-Ball +1

The paper introduces a stochastic smoothing proximal gradient algorithm for solving nonconvex‑nonconcave minimization‑expectation‑maximization (minEmax) problems, providing converg…

#stochastic optimization#nonconvex-nonconcave#minimax#distributionally robust optimization
math.OC2026

Stochastic Fleet Size and Mix Consistent Vehicle Routing Problem for Last Mile Delivery

Paolo Beatrici, Sebastian Birolini, Francesca Maggioni +1

The paper proposes a two‑stage stochastic mixed‑integer model that simultaneously decides the size and composition of a delivery fleet and the routing plan, adapting routes after a…

#fleet sizing#vehicle routing#stochastic optimization#mixed-integer programming