Titlebook: Exact Exponential Algorithms; Fedor V. Fomin,Dieter Kratsch Textbook 2010 Springer-Verlag Berlin Heidelberg 2010 Branching.Combinatorics.D

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Introduction, is a branching algorithm to compute a maximum independent set of a graph. The main idea of this algorithm can be traced back to the work of Miller and Muller [155] and Moon and Moser [161] from the nineteen sixties.

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Inclusion-Exclusion,n particular when direct counting is not possible. This counting principle is the main tool when designing inclusionexclusion algorithms. It seems that this algorithm design paradigm is suited very well to constructing fast exponential time algorithms since it naturally produces exponential time algorithms.

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Split and List,xponential size. The common way to enlarge the problem is to split the input into parts, and for each part to enumerate (or list) all possible solutions to subproblems corresponding to the part. Then we combine solutions of subproblems to solutions of the input of the original problem by making use of a fast polynomial time algorithm.

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Federated Learning for Wireless Networksof this chapter we discuss such an interpolation between the two extremes of space complexity for dynamic programming algorithms. In the second section we discuss an opposite technique to gain time by using more space, in particular for branching algorithms.

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Time Versus Space,of this chapter we discuss such an interpolation between the two extremes of space complexity for dynamic programming algorithms. In the second section we discuss an opposite technique to gain time by using more space, in particular for branching algorithms.

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Textbook 2010ynomial time, which means that the number of steps required for the algorithm to solve a problem is bounded by some polynomial in the length of the input. All other algorithms are slow (or bad). The running time of slow algorithms is usually exponential. This book is about bad algorithms. There are

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