Optimal Scheduling and Bidding of Flexibility for a Portfolio of Power System Assets in a Multi-Market Setting
Optimal non-anticipative scenarios for non-linear hydro-thermal power systems
Equilibrium prices for competitive electricity markets
Restarting Frank-Wolfe
[moved] New Methods for Regularization Path Optimization via Differential Equations
A Composite Randomized Incremental Gradient Method
Quasi-Variational Inequalities in Banach Spaces: Theory and Augmented Lagrangian Methods
On the Convexity of Optimal Control Problems involving Nonlinear PDEs or VIs
On quasi-variational inequality models arising in the description of sandpiles and river networks
Augmented Lagrangian Approaches for Solving Doubly Nonnegative Programming Problems
T.he B.undle A.pproach -- Scaling in ConicBundle 1.0 for Convex and Conic Optimization
Semidefinite Programming-Based Consistent Estimators for Shape-Constrained Regression
Convex Optimization Problems in Domain-Driven Form: Theory, Algorithms, and Software
Simulated Annealing with Hit-and-Run for Convex Optimization
alfonso: A new conic solver for convex optimization over non-symmetric cones
An outer-inner linearization method for non-convex and non-differentiable composite regularization problems
Relative-Error Inertial-Relaxed Inexact Versions of Douglas-Rachford and ADMM Splitting Algorithms
Projective Splitting with Co-coercive Operators
A DC algorithm for quadratic assignment problem
On the Equivalence of Inexact Proximal ALM and ADMM for a Class of Convex Composite Programming
Perturbation analysis of matrix optimization
Global optimization of noisy multimodal functions with RBF surrogates
Diagonal acceleration for covariance matrix adaptation evolution strategies
The evolution of RBFOpt: improving the RBF method, with one eye on performance
DC Formulations and Algorithms for Sparse Optimization Problems
On the Linear Convergence of DC Algorithms to Strong Stationary Points
Set optimization in systems biology: application to dynamic resource allocation problems
A scalarization scheme in ordered sets with applications to set-valued and robust optimization
Analysing the Role of the Inf-Sup Condition in Inverse Problems for Saddle Point Problems
A Universally Optimal Multistage Accelerated Stochastic Gradient Method
The importance of better models in stochastic optimization
Nonlinear Acceleration of Momentum and Primal-Dual Algorithms
Improved oracle complexity for stochastic compositional variance reduced gradient
On the Convergence of some Stochastic Primal-Dual Algorithms
Variance Reduction for Sums with Smooth and Nonsmooth Components with Linear Convergence
Eigenvalue perturbation theory in optimization: accuracy of computed eigenvectors and approximate semidefinite projection
Eliminations and cascading in nonlinear optimization
Interior point methods and preconditioners for PDE-constrained optimization
HiGHS: a high-performance linear optimizer
Solution of quadratic programming problems for fast approximate solution of linear programming problems
Solving large-scale doubly bordered block diagonal LPs in parallel
A discrete shape manifold and its use in PDE-constrained shape optimization
Increasing Sensitivity of Piezoelectric Ceramics by Electrode Shape Optimization
The phase field approach for topology optimization
Real-Time Approximations for Discretized Optimal Control Problems using Parametric Sensitivity Analysis
Optimal Control for a Nonconvex Sweeping Process with Applications to the Crowd Motion Model
Sufficiency for purely essentially bounded singular optimal controls
Inversion of Convection-Diffusion PDE with Discrete Sources
Adaptive Multilevel Optimization with Application to Fluid-Structure Interaction
Optimal boundary control of hyperbolic balance laws with state constraints
Computationally Efficient Approximations for Distributionally Robust Optimization
Bounds on Sums of Dependent Random Variables: An Optimization Approach
On the Heavy-Tail Behavior of the Distributionally Robust Newsvendor
Data-driven Approximate Dynamic Programming
Asymptotic Normality and Optimal Confidence Regions in Wasserstein Distributionally Robust Optimization
Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization
Deep learning as optimal control problems: models and numerical methods
Continuous optimisation of Gaussian mixture models in inverse problems
Iterative regularisation of continuous inverse problems via an entropic projection method
Optimal mini-batch and step sizes for SAGA
Acceleration of reduced variance stochastic gradient method
Stochastic Distributed Learning with Gradient Quantization and Variance Reduction