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'''Reward-based selection''' is a technique used in [[evolutionary algorithm]]s for selecting potenti Reward-based selection can be used within [[Multi-armed bandit]] framework for [[Multi-objective o ...

== Analysis of common parallel algorithms == ...l parallel algorithms for dynamic data redistribution, median finding, and selection|journal=Proceedings of the 10th IEEE International Parallel Processing Symp ...

...hat a person can only work on a single activity at a time. The '''activity selection problem''' is also known as the [[Interval scheduling|Interval scheduling m ...≥ ''f_j'' or ''s_j'' ≥ ''f_i''. The activity selection problem consists in finding the maximal solution set (S) of non-conflicting ...

...hat there exists (or that there can be constructed) a set of complementary algorithms. ...1016/j.artint.2016.04.003|title = ASlib: A benchmark library for algorithm selection|journal = Artificial Intelligence|volume = 237|pages = 41–58|year = 2016|la ...

...ion rate <math>r</math>. Search is intensified by a local [[random walk]]. Selection of the best continues until certain stop criteria are met. This essentially ...books?id=iVB_ETlh4ogC&q=bat+algorithm&pg=PR5 Nature-Inspired Metaheuristic Algorithms], 2nd Edition, Luniver Press, (2010).</ref> where a demo program in [[MATLA ...

...{Cite book|last=Lewis|first=R.|date=2021|title=A Guide to Graph Colouring: Algorithms and Applications|series=Texts in Computer Science |publisher=Springer|doi=1 ...upon. Much of the expense of this algorithm is due to Step 2, where vertex selection is made according to the heuristic rules stated above. Indeed, each time a ...

== Efficient algorithms == == Online algorithms == ...

...ath>x_M</math> in <math>X(t)</math> , normally realized using [[tournament selection]], which returns the best knowledge point from randomly selected <math>\tau ...(t)</math> into <math>X(t+1)</math>. A simple way is one by one tournament selection: for each knowledge point submitted by an agent, replace the worse one amon ...

{{About|the variable selection method|other uses|Counterfeit consumer goods}} ...nning for gold: model-X knockoffs for high dimensional controlled variable selection|journal=Journal of the Royal Statistical Society |series=Series B (methodol ...

...roximate counting algorithm]]s, the technique was later applied to a broad selection of [[Classification algorithm|classification]] and [[Regression analysis|re ...converge to solution very fast.{{sfn | Wang | Han | 2015 | p=11}} For the algorithms that are sublinear in space (e.g., counting the distinct elements of a stre ...

...(pp. 801-808). [https://papers.nips.cc/paper/2979-efficient-sparse-coding-algorithms.pdf]</ref> where the features are included based on the estimate of their s ...set, it can be a factor of <math>L</math> faster than the best alternative algorithms when this search is computationally expensive. A theorem<ref name="in_crow ...

==Algorithms== ...m matroid is well-studied in computer science as the [[Selection algorithm|selection problem]]. It may be solved in [[linear time]].<ref>{{citation ...

...Parallelism in algorithms and architectures |chapter=Fundamental parallel algorithms for private-cache chip multiprocessors |date=2008|pages=197–206|location=Ne ...Parallelism in algorithms and architectures |chapter=Fundamental parallel algorithms for private-cache chip multiprocessors |date=2008|pages=197–206|location=Ne ...

An unbiased random selection of individuals is important so that if many samples were drawn, the average ....<ref>Peters, Tim J., and Jenny I. Eachus. "Achieving equal probability of selection under various random sampling strategies." Paediatric and perinatal epidemi ...

...tribution]] when observations were limited. Subsequently, the optimization algorithms to solve this problem were improved<ref name='friedman'>{{cite journal ...

...into a single sorted list. These merge algorithms generally refer to merge algorithms that take in a number of sorted lists greater than two. Two-way merges are ...Rivest|authorlink3=Ron Rivest|author4=Clifford Stein|title=Introduction To Algorithms|url=https://books.google.com/books?id=NLngYyWFl_YC&pg=PA11|year=2001|publis ...

...ring algorithms do not typically produce any such labels. Cluster labeling algorithms examine the contents of the documents per cluster to find a labeling that s ...[mutual information]] and [[Pearson's chi-squared test|chi-squared feature selection]]. Terms having very low frequency are not the best in representing the wh ...

...f>{{cite book |first=X. S. |last=Yang |title=Nature-Inspired Metaheuristic Algorithms |publisher=[[Luniver Press]] |year=2008 |isbn=978-1-905986-10-1 }}</ref> ...ic and Evolutionary Computation |chapter=Metaheuristics in nature-inspired algorithms |year=2014|pages=1419–1422|chapter-url=http://www.macs.hw.ac.uk/~ml355/comm ...

...machine learning]] method designed to address the problem of [[best subset selection]]. It aims to determine which features or variables are crucial for optimal ...abess''' <ref name = "zhu2020"/> is employed to address the optimal subset selection problem in [[linear regression|general linear regression]]. '''abess''' is ...

...amentals of Deep Learning : Designing Next-Generation Machine Intelligence Algorithms |publisher=O'Reilly |isbn=978-1-4919-2558-4 |page=21 }}</ref> ...ice of Step Length, a Crucial Factor in the Performance of Variable Metric Algorithms |title=Numerical Methods for Non-linear Optimization |location=London |publ ...