Logistic regression is widely used in complex data analysis. When predictors are at individual level and the response at aggregate level, logistic regression can be estimated using the Maximum Likelihood Estimation (MLE) method with the joint likelihood function formed by Poisson binomial...

Introduction -- Primer of convex analysis -- Variational analysis -- Linear and nonlinear optimization problems -- Probability and Statistics -- Fundamental modeling questions in stochastic programming -- Adjusting to uncertainty: modeling recourse -- Probability constraints -- Proximal point...

The massive expansion of wind power and solar PV is the primary strategy to reduce greenhouse gas emissions in many countries. Due to their variable generation profiles, power sector flexibility needs to increase. Geographical balancing enabled by electricity grids and temporal flexibility...

The massive expansion of wind power and solar PV is the primary strategy to reduce greenhouse gas emissions in many countries. Due to their variable generation profiles, power sector flexibility needs to increase. Geographical balancing enabled by electricity grids and temporal flexibility...

Historical Note on Unconstrained Optimization and Quantum Calculus -- Basics of Unconstrained Optimization and Quantum Calculus -- Quantum-Steepest Descent Method with Quasi-Fejér Convergence -- Quantum- Fletcher-Reeves Conjugate Gradient Method -- Quantum-Polak-Ribière-Polyak -- Conjugate...