{"product_id":"algorithms-for-convex-optimization-hardback-9781108482028","title":"Algorithms for Convex Optimization (Hardback) 9781108482028","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eAlgorithms for Convex Optimization\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eA concise, accessible guide to the modern optimization methods that are transforming computer science, data science, and machine learning.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eNisheeth K. Vishnoi (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781108482028, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 7 October 2021\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e200 pages\u003cbr\u003e23.5 x 15.6 x 2.5 cm, 0.66 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e'Recommended.' M. Bona, Choice Connect\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eIn the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous optimization problems. For problems like maximum flow, maximum matching, and submodular function minimization, the fastest algorithms involve essential methods such as gradient descent, mirror descent, interior point methods, and ellipsoid methods. The goal of this self-contained book is to enable researchers and professionals in computer science, data science, and machine learning to gain an in-depth understanding of these algorithms. The text emphasizes how to derive key algorithms for convex optimization from first principles and how to establish precise running time bounds. This modern text explains the success of these algorithms in problems of discrete optimization, as well as how these methods have significantly pushed the state of the art of convex optimization itself.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e1. Bridging continuous and discrete optimization\u003cbr\u003e 2. Preliminaries\u003cbr\u003e 3. Convexity\u003cbr\u003e 4. Convex optimization and efficiency\u003cbr\u003e 5. Duality and optimality\u003cbr\u003e 6. Gradient descent\u003cbr\u003e 7. Mirror descent and multiplicative weights update\u003cbr\u003e 8. Accelerated gradient descent\u003cbr\u003e 9. Newton's method\u003cbr\u003e 10. An interior point method for linear programming\u003cbr\u003e 11. Variants of the interior point method and self-concordance\u003cbr\u003e 12. Ellipsoid method for linear programming\u003cbr\u003e 13. Ellipsoid method for convex optimization.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Algorithms \u0026amp; data structures [\u003ca title=\"See our other books on Algorithms \u0026amp; data structures\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Algorithms%20\u0026amp;%20data%20structures%20%5BUMB%5D%22\"\u003eUMB\u003c\/a\u003e], Optimization [\u003ca title=\"See our other books on Optimization\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Optimization%20%5BPBU%5D%22\"\u003ePBU\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":46005131837720,"sku":"9781108482028","price":78.79,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/products\/9781108482028i_fd416e44-01cd-46a2-8ec2-762327bdd8ea.jpg?v=1696706135","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/algorithms-for-convex-optimization-hardback-9781108482028","provider":"Freshly Printed Books","version":"1.0","type":"link"}