AI RESEARCH
A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method
arXiv CS.LG
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ArXi:2603.10230v1 Announce Type: cross In this paper, we propose a trust-region interior-point stochastic sequential quadratic programming (TR-IP-SSQP) method for solving optimization problems with a stochastic objective and deterministic nonlinear equality and inequality constraints. In this setting, exact evaluations of the objective function and its gradient are unavailable, but their stochastic estimates can be constructed.