Lev M. Bregman is a notable mathematician and researcher known for his work in various fields, particularly optimization, convex analysis, and related areas. He is recognized for developing the concept of Bregman divergence, a generalization of the notion of distance that is often used in optimization and machine learning contexts. Bregman divergence has applications in statistical learning theory and information geometry, among others.
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