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dc.contributor.authorShpilka, Amiren_US
dc.contributor.authorYehudayoff, Amiren_US
dc.date.accessioned2018-05-23T08:39:09Z
dc.date.available2018-05-23T08:39:09Z
dc.date.issued2010en_US
dc.identifier.otherHPU5161453en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/30925
dc.description.abstractA large class of problems in symbolic computation can be expressed as the task of computing some polynomials and arithmetic circuits form the most standard model for studying the complexity of such computations. This algebraic model of computation attracted a large amount of research in the last five decades, partially due to its simplicity and elegance. Being a more structured model than Boolean circuits, one could hope that the fundamental problems of theoretical computer science, such as separating P from NP, will be easier to solve for arithmetic circuits. However, in spite of the appearing simplicity and the vast amount of mathematical tools available, no major breakthrough has been seen. In fact, all the fundamental questions are still open for this model as well. Nevertheless, there has been a lot of progress in the area and beautiful results have been found, some in the last few years. As examples we mention the connection between polynomial identity testing and lower bounds of Kabanets and Impagliazzo, the lower bounds of Raz for multilinear formulas, and two new approaches for proving lower bounds: Geometric Complexity Theory and Elusive Functionsen_US
dc.format.extent184 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherNow publishers Incen_US
dc.subjectArithmetic Circuitsen_US
dc.subjectAlgorithms and Data Structuresen_US
dc.subjectTheoretical Computer Scienceen_US
dc.titleArithmetic Circuits (Foundations and Trends in Theoretical Computer Science)en_US
dc.typeBooken_US
dc.size1,003 KBen_US
dc.departmentTechnologyen_US


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