This textbook is an introduction to nonlinear optimization, which treats mathematical concepts stringently on the one hand, but also motivates them in great detail and illustrates them with 42 figures.
This textbook is an introduction to nonlinear optimization, which treats mathematical concepts stringently on the one hand, but also motivates them in great detail and illustrates them with 42 figures.
This book brings together cutting-edge research, methodologies, and applications in the field of optimization and nature-inspired computing, providing a comprehensive overview of the latest advancements and their applications in addressing contemporary challenges in engineering.
This book brings together cutting-edge research, methodologies, and applications in the field of optimization and nature-inspired computing, providing a comprehensive overview of the latest advancements and their applications in addressing contemporary challenges in engineering.
This book provides a rigorous introduction to the theory, computation, and applications of variational inequalities (VIs), with a focus on applications in management science and finance.
Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in SAS work.
This book offers a comprehensive compilation of research on the evaluation of the most environmentally and socially responsible financial institutions using a multiple criteria decision-making (MCDM) approach, with a focus on the principles of the Triple Bottom Line (TBL) model.
This book offers a comprehensive compilation of research on the evaluation of the most environmentally and socially responsible financial institutions using a multiple criteria decision-making (MCDM) approach, with a focus on the principles of the Triple Bottom Line (TBL) model.
Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization, and statistical estimation.
Because of its portability and platform-independence, Java is the ideal computer programming language to use when working on graph algorithms and other mathematical programming problems.
This book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering.
This book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering.
This book studies a general class of convex stochastic optimization (CSO) problems that unifies many common problem formulations from operations research, financial mathematics and stochastic optimal control.
This book studies a general class of convex stochastic optimization (CSO) problems that unifies many common problem formulations from operations research, financial mathematics and stochastic optimal control.
Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model.
Nonsmooth Optimization Methods and Applications provides an overview of this branch of mathematics, concentrating on the interaction between the theory and its applications.
Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vecto
This textbook is designed for a one-year graduate course in real algebraic geometry, with a particular focus on positivity and sums of squares of polynomials.
In a presentation that formalizes what makes up decision based design, Decision Based Design defines the major concepts that go into product realization.
Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language.
Several important problems arising in Physics, Differential Geometry and other topics lead to consider semilinear variational equations of strongly indefinite type and a great deal of work has been devoted to their study.
Nonsmooth Optimization Methods and Applications provides an overview of this branch of mathematics, concentrating on the interaction between the theory and its applications.
The game of Dots-and-Boxes, the popular game in which two players take turns connecting an array of dots to form squares, or boxes has long been considered merely a child's game.
Drawing on a comprehensive theoretical foundation encompassing socio-constructivism, social learning, and motivation, this book offers a new theoretical contribution and sheds light on the transformative power of acumenous game-based learning to reengage learners with Mathematics and Statistics Education.
This comprehensive technical guide explains game theory basics, architectures, protocols, security, models, open research issues, and cutting-edge advances and applications.
The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology.
