Continuous Optimization

This edition of the Continuous Optimization workshop aims to bring together leading experts from diverse backgrounds and career stages to discuss recent advances in the field. The program spans algorithms, theory and applications. Given the wide applicability of optimization in engineering (including machine learning as a prominent example) and the commonalities in mathematical tools used in other foundational fields (e.g., complexity theory, variational analysis, the dynamical systems view of iterative algorithms, the prevalence of various flavors of geometry and more), we expect renewed interactions with several other workshops, including Foundations of Data Science and Machine Learning, Computational Optimal Transport, Inverse Problems, Computational Algebraic Geometry, Random Matrices, Quantum Information and Quantum Algorithms, Computational Dynamics, and Numerical Linear Algebra.