methodology-8
Bilevel Optimization
3260 papers • 126 benchmarks • 313 datasets
Bilevel Optimization is a branch of optimization, which contains a nested optimization problem within the constraints of the outer optimization problem. The outer optimization task is usually referred as the upper level task, and the nested inner optimization task is referred as the lower level task. The lower level problem appears as a constraint, such that only an optimal solution to the lower level optimization problem is a possible feasible candidate to the upper level optimization problem. Source: Efficient Evolutionary Algorithm for Single-Objective Bilevel Optimization
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Most implemented papers
OptNet: Differentiable Optimization as a Layer in Neural Networks
J. Z. Kolter, Brandon Amos•Tue Feb 28 2017
OptNet is presented, a network architecture that integrates optimization problems (here, specifically in the form of quadratic programs) as individual layers in larger end-to-end trainable deep networks, and shows how techniques from sensitivity analysis, bilevel optimization, and implicit differentiation can be used to exactly differentiate through these layers.
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