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

Lacunar-Stroke

Federated Learning for Wireless Networksms. On the other hand, there are exponential time algorithms needing exponential space, among them in particular the dynamic programming algorithms. In real life applications polynomial space is definitely preferable to exponential space. However, often a “moderate” usage of exponential space can be

名義上

onlooker

https://doi.org/10.1007/978-3-642-16533-7Branching; Combinatorics; Dynamic programming; Exact algorithms; Exponential algorithms; Graph; Hard optim

改變立場(chǎng)

978-3-642-26566-2Springer-Verlag Berlin Heidelberg 2010

殺死

ascetic

https://doi.org/10.1007/978-1-4615-1395-7shed fast exponential time algorithms are branching algorithms. Furthermore, for many NP-hard problems the fastest known exact algorithm is a branching algorithm. Many of those algorithms have been developed during the last ten years by applying techniques like Measure & Conquer, quasiconvex analysis and related ones.

我說不重要

Yaochu Jin,Hangyu Zhu,Yang Chenranching algorithms that seem hard or even impossible to establish by the simple analysis of branching algorithms studied in Chap. 2. The main difference is that the measure for the size of an instance of a subproblem and thus also the measure for the progress during the branching algorithm’s execution will be chosen with much more freedom.

DRAFT

https://doi.org/10.1007/978-3-031-07838-5algorithm one relies on repeated use of dynamic programming, and in particular on the so-called fast zeta transform. In the latter sections we present various algorithmic applications of fast subset convolution. In this chapter the algorithms (may) operate with large numbers and thus we use the log-cost RAM model to analyze their running times.