Sensitivity and stability analysis for nonlinear programming

By A. Fiacco, Y. Ishizuka. 1991

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OptNet: Differentiable Optimization as a Layer in Neural Networks (2017, neutral): “These techniques also come up in bilevel optimization (Gould et al., 2016; Kunisch & Pock, 2013) and sensitivity analysis (Bertsekas, 1999; Fiacco & Ishizuka, 1990; Bonnans & Shapiro, 2013).”
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions (2019, unknown): “(Fiacco & Ishizuka, 1990) Let w0 solve Problem 4b for λ0.”
Delta-method inference for a class of set-identified SVARs (2018, methodology): “We relate the expression of the directional derivative with the generalized versions of the envelope theorems in the work of Fiacco and Ishizuka (1990) and Bonnans and Shapiro (2000).”
Process optimization via constraints adaptation (2008, methodology): “We start the analysis with a number of definitions relative to the parametric programming problem Ph(Æ) [24,25].”
An Actor-Critic Contextual Bandit Algorithm for Personalized Mobile Health Interventions (2017, methodology): “Indeed JITAIs have received increasing popularity and have been used to support health behavior change in a variety of domains including physical activity (King et al. (2013); Consolvo et al.”
CasADi: a software framework for nonlinear optimization and optimal control (2018, unknown): “[43], directional derivatives of an NLP solver object are guarenteed to exist and can be calculated using information that can be extracted from the expression graphs.”