Here are some of his notable works:
Books:
* Nonlinear Programming (1969): This book is considered a classic in the field of optimization and provides a comprehensive treatment of nonlinear programming techniques.
* Machine Learning via Polyhedral Concave Minimization (1997): This book presents a unique approach to machine learning based on polyhedral concave minimization.
* Machine Learning: A Mathematical Programming Approach (2014): This book offers a mathematical perspective on machine learning and explores connections between optimization and machine learning algorithms.
Articles:
Mangasarian has also published hundreds of research articles in prestigious journals like:
* Mathematical Programming
* Operations Research
* SIAM Journal on Optimization
* Journal of Machine Learning Research
* IEEE Transactions on Neural Networks
* Data Mining and Knowledge Discovery
His research interests cover a wide range of topics, including:
* Linear and Nonlinear Programming: Theory, algorithms, and applications
* Machine Learning: Classification, regression, dimensionality reduction, and feature selection
* Artificial Intelligence: Expert systems, neural networks, and fuzzy logic
* Data Mining: Pattern recognition, clustering, and outlier detection
* Computational Optimization: Convex optimization, nonconvex optimization, and combinatorial optimization
Mangasarian's work has had a significant impact on the fields of optimization and machine learning. He has been recognized for his contributions with numerous awards and honors, including the John von Neumann Theory Prize from the INFORMS and the SIAM Prize for Distinguished Service to the Profession.