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Stationarity and Convergence in Reduce-or-Retreat Minimization
Adam B. Levy
€ 59.18
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Description for Stationarity and Convergence in Reduce-or-Retreat Minimization
Paperback. Presents and analyzes a unifying framework for a wide variety of numerical methods in optimization. This title covers various derivative-based methods within the same framework encourages the construction of new methods, and inspires new theoretical developments as companions to results from across traditional divides. Series: SpringerBriefs in Optimization. Num Pages: 67 pages, 2 black & white illustrations, 1 colour illustrations, 1 black & white tables, biography. BIC Classification: PBKQ; PBKS; PBT; PBU. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 5. Weight in Grams: 122.
Stationarity and Convergence in Reduce-or-Retreat Minimization presents and analyzes a unifying framework for a wide variety of numerical methods in optimization. The author’s “reduce-or-retreat” framework is a conceptual method-outline that covers any method whose iterations choose between reducing the objective in some way at a trial point, or retreating to a closer set of trial points. The alignment of various derivative-based methods within the same framework encourages the construction of new methods, and inspires new theoretical developments as companions to results from across traditional divides. The text illustrates the former by developing two generalizations of classic derivative-based methods which accommodate non-smooth ... Read more
Stationarity and Convergence in Reduce-or-Retreat Minimization presents and analyzes a unifying framework for a wide variety of numerical methods in optimization. The author’s “reduce-or-retreat” framework is a conceptual method-outline that covers any method whose iterations choose between reducing the objective in some way at a trial point, or retreating to a closer set of trial points. The alignment of various derivative-based methods within the same framework encourages the construction of new methods, and inspires new theoretical developments as companions to results from across traditional divides. The text illustrates the former by developing two generalizations of classic derivative-based methods which accommodate non-smooth ... Read more
Product Details
Format
Paperback
Publication date
2012
Publisher
Springer-Verlag New York Inc. United States
Number of pages
67
Condition
New
Series
SpringerBriefs in Optimization
Number of Pages
55
Place of Publication
New York, NY, United States
ISBN
9781461446415
SKU
V9781461446415
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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