Cynthia Dwork , Aaron Roth. The Algorithmic Foundations of Differential Privacy. David P. Sketching as a Tool for Numerical Linear Algebra. Sushant Sachdeva , Nisheeth K. Faster Algorithms via Approximation Theory. Nisheeth K. Stasys Jukna , Igor Sergeev. Complexity of Linear Boolean Operators.
Data Streams: Algorithms and Applications (Foundations and Trends in Theoretical Computer Science,)
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Sergey Yekhanin. Locally Decodable Codes. Partial Derivatives in Arithmetic Complexity and Beyond. Amir Shpilka , Amir Yehudayoff. Arithmetic Circuits: A survey of recent results and open questions. Troy Lee , Adi Shraibman.
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Lower Bounds in Communication Complexity. Dana Ron. Algorithmic and Analysis Techniques in Property Testing. Satyanarayana V. Complexity Lower Bounds using Linear Algebra. Emanuele Viola. On the Power of Small-Depth Computation.
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Jeffrey Scott Vitter. Algorithms and Data Structures for External Memory. Dieter van Melkebeek. Andrej Bogdanov , Luca Trevisan. Average-Case Complexity. Venkatesan Guruswami. Nisheeth K. Home Contact us Help Free delivery worldwide. Free delivery worldwide. Bestselling Series. Harry Potter. Popular Features. New Releases. Description A 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 the authors of this book 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.
Arithmetic Circuits Foundations And Trends In Theoretical Computer Science
The goal of this monograph is to survey the field of arithmetic circuit complexity, focusing mainly on what they find to be the most interesting and accessible research directions. They cover the main results and techniques, with an emphasis on works from the last two decades. In particular, they discuss the recent lower bounds for multilinear circuits and formulas, the advances in the question of deterministically checking polynomial identities, and the results regarding reconstruction of arithmetic circuits. This book also covers part of the classical works on arithmetic circuits and in order to keep it at a reasonable length, the authors do not give full proofs of most theorems, but rather try to convey the main ideas behind each proof and demonstrate it, where possible, by proving some special cases.
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Bayesian Mechanism Design Jason D. Probabilistic Proof Systems Oded Goldreich. Quantum Proofs Thomas Vidick. Locally Decodable Codes Sergey Yekhanin. Average-Case Complexity Andrej Bogdanov. Spectral Algorithms Ravindran Kannan.