GRAPH THEORY AND COMPUTATIONAL COMPLEXITYFor, AlgorithmsDesign, Vlsi
and societal phenomena.\nComputational Complexity: Theory, Techniques and Applications presents a detailed and integrated view of the theoretical basis, computational methods, and state-of-the-art approaches to investigating and modeling of inherently difficult problems whose solution requires extensive resour...
Concepts from computational complexity theory can be directly applied to the computations that brains must accomplish. For example, one well-known combinatorial optimization problem, the traveling salesman problem, has proven relevant to the analysis of spatial cognition and the diagnoses of cognitive ...
In theoretical computer science, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of...
Praise for the First Edition "... complete, up-to-date coverage of computational complexity theory...the book promises to become the standard reference on computational complexity."—Zentralblatt MATH
A computational problem is defined as a task that needs to be solved using a computer, and it is classified based on its inherent difficulty in terms of computational complexity theory. AI generated definition based on: Computers in Biology and Medicine, 2015 About this pageSet alert Also in ...
This chapter describes a theory of computational complexity that yields insights into how difficult a problem may be to solve. For most integer programming problems, no such algorithm is known. The chapter shows that there are integer programming problems much more specific than the general pure-int...
Data Structures, Cryptology and Information Theory Keywords Graph vulnerability Parameterized complexity Complexity Graph algorithms Preprocessing Industry Sectors Aerospace Electronics IT & Software Telecommunications Authors Pål Grønås Drange (1) Markus Dregi (1) Pim van ’t Hof (1) Au...
computational complexity is brought into the picture. Assuming reasonable complexity-theoretic conjectures, we show that derivatives can actually amplify the costs of asymmetric information instead of reducing them. We prove our results both in the worst-case setting, as well as the more realistic aver...
BIG 4. Matching in Polynomial Time. (Edmonds 1965, Canadian Journal of Mathematics) Poly time seen as important. BIG. 5. Matrix Multiplication in O(n2.87) time (less than n3 !!) (Strassen 1969). 6. The Speed Up Theorem–There are decidable sets that cannot be assigned a complexity int...