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| Preface | ||
| Contributors | ||
| Discretization and Mesh-Independence of Newton's Method for Generalized Equations | 1 | |
| Extended Quadratic Tangent Optimization Problems | 31 | |
| On Generalized Differentiability of Optimal Solutions in Nonlinear Parametric Optimization | 47 | |
| Characterizations of Lipschitzian Stability in Nonlinear Programming | 65 | |
| On Second Order Sufficient Conditions for Structured Nonlinear Programs in Infinite-Dimensional Function Spaces | 83 | |
| Algorithmic Stability Analysis for Certain Trust Region Methods | 109 | |
| A Note on Using Linear Knowledge to Solve Efficiently Linear Programs Specified with Approximate Data | 133 | |
| On the Role of the Mangasarian-Fromovitz Constraint Qualification for Penalty-, Exact Penalty-, and Lagrange Multiplier Methods | 159 | |
| Hoffman's Error Bound for Systems of Convex Inequalities | 185 | |
| Lipschitzian and Pseudo-Lipschitzian Inverse Functions and Applications to Nonlinear Optimization | 201 | |
| On Well-Posedness and Stability Analysis in Optimization | 223 | |
| Convergence of Approximations to Nonlinear Optimal Control Problems | 253 | |
| A Perturbation-Based Duality Classification for Max-Flow Min-Cut Problems of Strang and Iri | 285 | |
| Central and Peripheral Results in the Study of Marginal and Performance Functions | 305 | |
| Topological Stability of Feasible Sets in Semi-infinite Optimization: A Tutorial | 339 | |
| Solution Existence for Infinite Quadratic Programming | 363 | |
| Sensitivity Analysis of Nonlinear Programming Problems via Minimax Functions | 387 | |
| Parametric Linear Complementarity Problems | 399 | |
| Sufficient Conditions for Weak Sharp Minima of Order Two and Directional Derivatives of the Value Function | 419 | |
| Index | 437 |
| Price | Condition | Delivery | Seller | Action |
| $259.15 | Digital |
| WonderClub |
Matthew Duncan
reviewed Mathematical Programming with Data Perturbations, Vol. 195 on August 28, 2015
Mathematical Programming with Data Perturbations
I normally don't do this, but I'm going to copy/paste this review across three separate books: Chaitin's "The Unknowable", "The Limits of Mathematics", and "Exploring Randomness".
All three are all thin, overpriced, but very approachable books on Algorithmic Information Theory. Themes include:
- Undecidability, as the basis of formulating a new kind of randomness measure for numbers that have already been generated (not just restricting randomness measures to the processes that generate numbers).
- Chaitin's Omega constant, which is the probability that universal Turning machine will halt on random input. This constant is "maximally unknowable", but that doesn't stop one from performing math with it.
- Philosophy surrounding these topics.
One might underestimate Kolmogorov's contributions, given how ridiculously self-promoting Chaitin has been with this AIT. However, the topics are interesting enough that he's easy to forgive. And he uses many code demonstrations (LISP) to make concrete examples out of the math.
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Add Mathematical Programming with Data Perturbations, Vol. 195, Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings , Mathematical Programming with Data Perturbations, Vol. 195 to the inventory that you are selling on WonderClubX
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Add Mathematical Programming with Data Perturbations, Vol. 195, Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings , Mathematical Programming with Data Perturbations, Vol. 195 to your collection on WonderClub |