e-books in Computational Complexity Theory category
by Alexander Shen - arXiv.org , 2015
Algorithmic information theory studies description complexity and randomness. This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, etc.
by Tim Roughgarden - Stanford University , 2015
The two biggest goals of the course are: 1. Learn several canonical problems that have proved the most useful for proving lower bounds; 2. Learn how to reduce lower bounds for fundamental algorithmic problems to communication complexity lower bounds.
by F. D. Lewis - University of Kentucky , 2013
This is an on-line textbook on heuristic algorithms. From the table of contents: Classes of Problems; Integer Programming; Enumeration Techniques; Dynamic Programming; Approximate Solutions; Local Optimization; Natural Models.
- Wikibooks , 2010
This book is intended as an introductory textbook in Computability Theory and Complexity Theory, with an emphasis on Formal Languages. Its target audience is CS and Math students with some background in programming and data structures.
by Oded Goldreich - Cambridge University Press , 2010
The main focus of the current book is on the P-vs-NP Question and the theory of NP-completeness. Additional topics that are covered include the treatment of the general notion of a reduction between computational problems.
by Allen B. Downey - Green Tea Press , 2012
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science. The book focuses on discrete models, which include graphs, cellular automata, and agent-based models.
by Ian Parberry - Prentice Hall , 1987
The rapid growth of parallel complexity theory has led to a proliferation of parallel machine models. This book presents a unified theory of parallel computation based on a network model. It is the first such synthesis in book form.
by Karl Petersen - University of North Carolina , 2008
These notes provide an introduction to the subject of measure-preserving dynamical systems, discussing the dynamical viewpoint; how and from where measure-preserving systems arise; the construction of measures and invariant measures; etc.
by R. G. Downey, D. R. Hirschfeldt - Springer , 2010
Computability and complexity theory are two central areas of research in theoretical computer science. This book provides a systematic, technical development of algorithmic randomness and complexity for scientists from diverse fields.
by Leslie Lamport - Addison-Wesley Professional , 2002
This book shows how to write unambiguous specifications of complex computer systems. It provides a complete reference manual for the TLA+, the language developed by the author for writing simple and elegant specifications of algorithms and protocols.
by Neil D. Jones - The MIT Press , 1997
The author builds a bridge between computability and complexity theory and other areas of computer science. Jones uses concepts familiar from programming languages to make computability and complexity more accessible to computer scientists.
by Oded Goldreich - Cambridge University Press , 2007
The book gives the mathematical underpinnings for cryptography; this includes one-way functions, pseudorandom generators, and zero-knowledge proofs. Throughout, definitions are complete and detailed; proofs are rigorous and given in full.
by Oded Goldreich - Cambridge University Press , 2008
This book offers a comprehensive perspective to modern topics in complexity theory. It can be used as an introduction as either a textbook or for self-study, or to experts, since it provides expositions of the various sub-areas of complexity theory.
by Ben Goertzel - Plenum Press , 1996
This text applies the concepts of complexity science to provide an explanation of all aspects of human creativity. The book describes the model that integrates ideas from computer science, mathematics, neurobiology, philosophy, and psychology.
by Allen Downey - Green Tea Press , 2011
This book is about data structures and algorithms, intermediate programming in Python, complexity science and the philosophy of science. The book covers Graphs, Analysis of algorithms, Scale-free networks, Cellular Automata, Agent-based models, etc.
by Luca Trevisan , 2004
Notes from a graduate courses on Computational Complexity. The first 15 lectures cover fundamentals, the remaining is advanced material: Hastad's optimal inapproximability results, lower bounds for parity in bounded depth-circuits, and more.
by Martin Tompa , 1991
Lecture notes for a graduate course on computational complexity taught at the University of Washington. Alternating Turing machines are introduced very early, and deterministic and nondeterministic Turing machines treated as special cases.
by Oded Goldreich , 1999
Complexity theory is the study of the intrinsic complexity of computational tasks. The book is aimed at exposing the students to the basic results and research directions in the field. The focus was on concepts, complex technical proofs were avoided.
by Sanjeev Arora, Boaz Barak - Cambridge University Press , 2008
The book provides an introduction to basic complexity classes, lower bounds on resources required to solve tasks on concrete models such as decision trees or circuits, derandomization and pseudorandomness, proof complexity, quantum computing, etc.
by Johan Håstad , 2008
This set of notes gives the broad picture of modern complexity theory, defines the basic complexity classes, gives some examples of each complexity class and proves the most standard relations. The author emphasizes the ideas involved in the proofs.
by Herbert S. Wilf - AK Peters, Ltd. , 1994
An introductory textbook on the design and analysis of algorithms. Recursive algorithms are illustrated by Quicksort, FFT, and fast matrix multiplications. Algorithms in number theory are discussed with some applications to public key encryption.