Nonlinear Programming

Third edition

• Extensive coverage of iterative optimization methods within a unifying framework
• Duality theory from both a variational and a geometric point of view
• Detailed treatment of interior point methods for linear programming
• New material on a number of topics, such as proximal algorithms, alternating direction methods of multipliers, and conic programming
• Large-scale optimization topics of much current interest, such as first order methods, incremental methods, and distributed asynchronous computation, and their applications in machine learning, signal processing, neural network training, and big data applications

Errata and comments

Coming soon.