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Based on undergraduate teaching to students in computer science,
economics and mathematics at Aarhus University, this is an
elementary introduction to convex sets and convex functions with
emphasis on concrete computations and examples.Starting from linear
inequalities and Fourier-Motzkin elimination, the theory is
developed by introducing polyhedra, the double description method
and the simplex algorithm, closed convex subsets, convex functions
of one and several variables ending with a chapter on convex
optimization with the Karush-Kuhn-Tucker conditions, duality and an
interior point algorithm. Study Guide here
Based on undergraduate teaching to students in computer science,
economics and mathematics at Aarhus University, this is an
elementary introduction to convex sets and convex functions with
emphasis on concrete computations and examples.Starting from linear
inequalities and Fourier-Motzkin elimination, the theory is
developed by introducing polyhedra, the double description method
and the simplex algorithm, closed convex subsets, convex functions
of one and several variables ending with a chapter on convex
optimization with the Karush-Kuhn-Tucker conditions, duality and an
interior point algorithm. Study Guide here
Niels Lauritzen's approach to simplify the teaching of abstract algebra is based on the extensive use of examples, applications and exercises. The book contains novel applications (for example, RSA encoding) as well as a treatment of Gröbner bases at an undergraduate level.
Niels Lauritzen's approach to simplify the teaching of abstract algebra is based on the extensive use of examples, applications and exercises. The book contains novel applications (for example, RSA encoding) as well as a treatment of Gröbner bases at an undergraduate level.
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