The fields of machine learning and mathematical programming are increasingly intertwined.
Optimization problems lie at the heart of most machine learning approaches. The Special …

An Introduction to Optimization Accessible introductory textbook on optimization theory and
methods, with an emphasis on engineering design, featuring MATLAB® exercises and …

An up-to-date account of the interplay between optimization and machine learning,
accessible to students and researchers in both communities. The interplay between …

The goal of this tutorial is to introduce key models, algorithms, and open questions related to
the use of optimization methods for solving problems arising in machine learning. It is written …

This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …

Machine learning develops rapidly, which has made many theoretical breakthroughs and is
widely applied in various fields. Optimization, as an important part of machine learning, has …

This monograph presents the main mathematical ideas in convex optimization. Starting from
the fundamental theory of black-box optimization, the material progresses towards recent …

The field of optimization is interdisciplinary in nature, and has been making a significant
impact on many disciplines. As a result, it is an indispensable tool for many practitioners in …

This paper surveys the recent attempts, both from the machine learning and operations
research communities, at leveraging machine learning to solve combinatorial optimization …

A frequent challenge faced by beginners in machine learning is the extensive background
required in linear algebra and optimization. One problem is that the existing linear algebra …