However, graph classes that are hard for one algorithm turn out to be easy for others. In most cases our bounds show that reoptimization is faster than optimizing from scratch. We further show that tailoring mutation operators to parts of the graph where changes have occurred can significantly ...
Since each message contains one bit, we deduce the same values for its bit complexity. Then we combine this algorithm with another and we obtain a 3-colouring algorithm for ring graphs. Thanks to an overlapping, we obtain once more the same values for the time complexities on average and ...
TIME COMPLEXITY: The time complexity of the algorithm is O(2^n), where n is the number of variables. This exponential time complexity arises due to the recursive nature of the algorithm, where each variable can have two possible values (true or false). USAGE : • Compile and run the p...
Merge Sort Algorithm is considered as one of the best sorting algorithms having a worst case and best case time complexity of O(N*Log(N)), this is the reason that generally we prefer to merge sort over quicksort as quick sort does have a worst-case time complexity of O(N*N)...
Eikelder HM, Willemen RJ.Some complexity aspects of secondary school timetabling problems. Computer Science Practice and Theory of Automated Timetabling III. Lecture Notes in Computer Science, 2001; 2079:18–27. Emma Hart, Jon Timmis, Application areas of AIS: The past, the present and the futu...
The graph coloring algorithm is subject to the same requirements as the resource alloca- tion algorithm: it must be scalable, real-time, adaptive and robust. Details of how the satisfaction of these requirements can be formally assessed are presented below; for now, ...
Deterministic polynomial-time approximation algorithms for partition functions and graph polynomialsMathematics - CombinatoricsComputer Science - Computational ComplexityComputer Science - Discrete MathematicsComputer Science - Data Structures and AlgorithmsIn this paper we show a new way of constructing ...
TL;DR: This is an informal summary of our recent paperPrincipled Deep Neural Network Training through Linear ProgrammingwithDan BienstockandGonzalo Muñoz, where we show that the computational complexity of approximate Deep Neural Network training depends polynomially on the data size for several archit...
Errors in numeric data also may be obvious, such as for a singularly misplaced point in an otherwise smooth graph. Errors in financial data can be catastrophic. Error handling is generally discussed in terms of detection and correction, with implementation scheme complexity proportional to the ...
TST switching fabrics are commonly used to reduce physical complexity in time division multiplexed (TDM) switching systems. An n-port, m-timeslot TST switching fabric receives a different input signal at each one of the fabric's n ingress ports. Each input signal is time-divided into “timesl...