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000728371 020__ $$a9783319212753$$qelectronic book
000728371 020__ $$a3319212753$$qelectronic book
000728371 020__ $$z9783319212746
000728371 0247_ $$a10.1007/978-3-319-21275-3$$2doi
000728371 035__ $$aSP(OCoLC)ocn915052438
000728371 035__ $$aSP(OCoLC)915052438
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000728371 050_4 $$aQA276.8$$b.P37 2015eb
000728371 08204 $$a519.5/44$$223
000728371 24500 $$aParameterized algorithms$$h[electronic resource] /$$cMarek Cygan, Fedor V. Fomin, Łukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michał Pilipczuk, Saket Saurabh.
000728371 264_1 $$aCham :$$bSpringer,$$c2015.
000728371 300__ $$a1 online resource (xvii, 613 pages) :$$billustrations.
000728371 336__ $$atext$$btxt$$2rdacontent
000728371 337__ $$acomputer$$bc$$2rdamedia
000728371 338__ $$aonline resource$$bcr$$2rdacarrier
000728371 504__ $$aIncludes bibliographical references and indexes.
000728371 5050_ $$aIntroduction -- Kernelization -- Bounded Search Trees -- Iterative Compression -- Randomized Methods in Parameterized Algorithms -- Miscellaneous -- Treewidth -- Finding Cuts and Separators -- Advanced Kernelization Algorithms -- Algebraic Techniques: Sieves, Convolutions, and Polynomials -- Improving Dynamic Programming on Tree Decompositions -- Matroids -- Fixed-Parameter Intractability -- Lower Bounds Based on the Exponential-Time Hypothesis -- Lower Bounds for Kernelization.
000728371 506__ $$aAccess limited to authorized users.
000728371 520__ $$aThis comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way. The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds. All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.
000728371 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 29, 2015).
000728371 650_0 $$aParameter estimation.
000728371 650_0 $$aComputer algorithms.
000728371 650_0 $$aComputer science$$xMathematics.
000728371 7001_ $$aCygan, Marek,$$d1984-$$eauthor.
000728371 7001_ $$aFomin, Fedor V.,$$eauthor.
000728371 7001_ $$aKowalik, Łukasz,$$eauthor.
000728371 7001_ $$aLokshtanov, Daniel,$$eauthor.
000728371 7001_ $$aMarx, Daniel,$$cDr.,$$eauthor.
000728371 7001_ $$aPilipczuk, Marcin,$$eauthor.
000728371 7001_ $$aPilipczuk, Michał$$eauthor.
000728371 7001_ $$aSaurabh, Saket,$$eauthor.
000728371 852__ $$bebk
000728371 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-21275-3$$zOnline Access$$91397441.1
000728371 909CO $$ooai:library.usi.edu:728371$$pGLOBAL_SET
000728371 980__ $$aEBOOK
000728371 980__ $$aBIB
000728371 982__ $$aEbook
000728371 983__ $$aOnline
000728371 994__ $$a92$$bISE