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Evolutionary Algorithms and Submodular Functions: Benefits of Heavy-Tailed Mutations [article]

Tobias Friedrich and Andreas Göbel and Francesco Quinzan and Markus Wagner
2018 arXiv   pre-print
A core feature of evolutionary algorithms is their mutation operator. Recently, much attention has been devoted to the study of mutation operators with dynamic and non-uniform mutation rates.  ...  Following up on this line of work, we propose a new mutation operator and analyze its performance on the (1+1) Evolutionary Algorithm (EA).  ...  We denote with opt any solution of Problem (3) , and we denote with n the size of V . Heavy-tailed mutations are useful.  ... 
arXiv:1805.10902v2 fatcat:34o2slnwqzcmrlstdpzpavzfku

Multi-objective Evolutionary Algorithms are Still Good: Maximizing Monotone Approximately Submodular Minus Modular Functions [article]

Chao Qian
2019 arXiv   pre-print
As evolutionary algorithms (EAs) are general-purpose optimization algorithms, recent theoretical studies have tried to analyze their performance for solving general problem classes, with the goal of providing  ...  monotone approximately submodular function and c is a non-negative modular function, resulting in the objective function f being non-monotone non-submodular.  ...  EAs submodular non-submodular monotone (Friedrich and Neumann, 2015) non-monotone (Friedrich and Neumann, 2015) This work (Friedrich et al., 2018) that the (1+1)-EA using a heavy-tailed mutation  ... 
arXiv:1910.05492v1 fatcat:5gd57rfacnh2biagut5aya7wbq

Coevolutionary Pareto Diversity Optimization [article]

Aneta Neumann, Denis Antipov, Frank Neumann
2022 arXiv   pre-print
sampling and improving the diversity of the set of solutions afterwards.  ...  We show that our standard co-evolutionary Pareto Diversity Optimization approach outperforms the recently introduced DIVEA algorithm which obtains its initial population by generalized diversifying greedy  ...  Acknowledgements This work has been supported by the Australian Research Council (ARC) through grants DP190103894, FT200100536, and by the South Australian Government through the Research Consortium "Unlocking  ... 
arXiv:2204.05457v1 fatcat:rl66avdm4jfarexf6d42ysfmfm

Coevolutionary Pareto diversity optimization

Aneta Neumann, Denis Antipov, Frank Neumann
2022 Proceedings of the Genetic and Evolutionary Computation Conference  
sampling and improving the diversity of the set of solutions afterwards.  ...  We show that our standard co-evolutionary Pareto Diversity Optimization approach outperforms the recently introduced DIVEA algorithm which obtains its initial population by generalized diversifying greedy  ...  ACKNOWLEDGEMENTS This work has been supported by the Australian Research Council (ARC) through grants DP190103894, FT200100536, and by the South Australian Government through the Research Consortium "Unlocking  ... 
doi:10.1145/3512290.3528755 fatcat:6jywo2gxifho3jsadgxcboctdy

Specific Single- and Multi-Objective Evolutionary Algorithms for the Chance-Constrained Knapsack Problem [article]

Yue Xie, Aneta Neumann, Frank Neumann
2020 arXiv   pre-print
We examine the use of heavy-tail mutations and introduce a problem-specific crossover operator to deal with the chance-constrained knapsack problem.  ...  Empirical results for single-objective evolutionary algorithms show the effectiveness of our operators compared to the use of classical operators.  ...  Then we examine the impact of the heavy-tail mutation operator in the algorithm.  ... 
arXiv:2004.03205v2 fatcat:c6nlrbisebgj3nzyrnyyrknsom

Evolutionary Algorithms for the Chance-Constrained Knapsack Problem [article]

Yue Xie, Oscar Harper, Hirad Assimi, Aneta Neumann, Frank Neumann
2021 arXiv   pre-print
In the experiment section, we evaluate and compare the deterministic approaches and evolutionary algorithms on a wide range of instances.  ...  Evolutionary algorithms have been applied to a wide range of stochastic problems.  ...  [46] investigated the performance of evolutionary algorithms combined with a heavy-tail mutation operator and a problem-specific crossover operator.  ... 
arXiv:1902.04767v3 fatcat:3mh2o7dwmbftdkkfjkmplbekxy

Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms

Rudolf Jagdhuber, Michel Lang, Arnulf Stenzl, Jochen Neuhaus, Jörg Rahnenführer
2020 BMC Bioinformatics  
In this paper, we propose extensions to two feature selection methods to control the total amount of such costs: greedy forward selection and genetic algorithms.  ...  Adaptations of these algorithms such as the ones proposed in this paper can help to tackle this problem.  ...  Instead we use a more complex distribution with heavy tails and more extreme values.  ... 
doi:10.1186/s12859-020-3361-9 pmid:31992203 pmcid:PMC6986087 fatcat:a2zerttiazgjzpwukze7p4mjiq

Mathematical and Algorithmic Analysis of Network and Biological Data [article]

Charalampos E. Tsourakakis
2014 arXiv   pre-print
This dissertation contributes to mathematical and algorithmic problems that arise in the analysis of network and biological data.  ...  These heavy tailed empirical distributions are frequently modeled as power laws. Definition 1.1.  ...  Kronecker graphs match several empirical properties such as heavy-tailed degree distributions and triangles, low diameters, and also obeys the densification power law.  ... 
arXiv:1407.0375v1 fatcat:6s2qka5fazbl7bzxz4k3u75hzm

Abstracts of Working Papers in Economics

1994 Abstracts of Working Papers in Economics  
We start by reassessing specification and sample period sensitivities that have made many economists question the usefulness of this statistical framework.  ...  We show that contrary to the claims of some researchers, the money-output relationship does not break down in the 1980's and M2 helps forecast output into the early 1990's.  ...  There are many situations, however, in which an auction's participants interact after the close of the auction, and where the outcome of the auction affects the nature of their future interaction.  ... 
doi:10.1017/s0951007900004307 fatcat:6n5cem2tx5a3picfojgf6vmxfe

Abstracts of Working Papers in Economics

1997 Abstracts of Working Papers in Economics  
This section contains abstracts and complete bibliographic information for current working papers, listed alphabetically by primary author.  ...  This unusual result is due to the effect of the initial sample observations that are typically neglected in theoretical asymptotic analysis, in spile of their empirical relevance.  ...  It is found that robustness depends on the contemporaneous covariance between the disturbances of the cointegrating regression and the shocks driving the regressors and on the extent of the deviation from  ... 
doi:10.1017/s0951007900003430 fatcat:oihawd6jxbdrbipl5wzi254txi

Dagstuhl Reports, Volume 5, Issue 8, August 2015, Complete Issue [article]

2016
-Present and Future of Formal Argumentation and Abstract Dialectical Frameworks (ADFs).  ...  We would like to thank Dagmar Glaser and the staff at Schloss Dagstuhl for their continuous support and great hospitality which was the basis for the success of this seminar.  ...  A minimum error entropy method takes moments of all orders into consideration and may perform well in dealing with heavy-tailed noise.  ... 
doi:10.4230/dagrep.5.8 fatcat:7nxac5wvjndalneozxtrwminya

Tuning Hyperparameters without Grad Students: Scaling up Bandit Optimisation

Kirthevasan Kandasamy
2019
Typically, each experiment incurs a large computational or economic cost, and we need to keep the number of experiments to a minimum.  ...  Many of suchproblems fall under the bandit framework, where the outcome of each experiment can be viewed as a reward signal, and the goal is to optimise for this reward, i.e. findthe design that maximises  ...  This includes an evolutionary algorithm to optimise the acquisition function.  ... 
doi:10.1184/r1/8337638 fatcat:4pywy7au3vfulaoccsuzbzn2my

Abstracts of Working Papers in Economics

2001 Abstracts of Working Papers in Economics  
A stochastic frontier production function framework in used to assess the relative productivity of 113 university TTOs.  ...  Environmental and institutional factors appear to explain some of the variation in TTO efficiency.  ...  State Dependent Mutation. Risk Dominance. Local Interaction Games. Evolutionary Game Theory. TI Should Unemployment Benefits Decrease With Unemployment Spell?  ... 
doi:10.1017/s0951007900005271 fatcat:z6i2zndgbvazdmfeb5py5o5smi

Information-theoretic causal inference of lexical flow [article]

Johannes Dellert, Universitätsbibliothek Der FU Berlin, Universitätsbibliothek Der FU Berlin
2019
on the opening and closing of directional contact channels as primary evolutionary events.  ...  The algorithms are evaluated both against a large lexical database of Northern Eurasia spanning many language families, and against simulated data generated by a new model of language contact that builds  ...  This requires the generation of trees to be modeled explicitly by an evolutionary model, which can e.g. include separate mutation rates for each branch.  ... 
doi:10.17169/refubium-25627 fatcat:es7wyld6sbc3nf3esdfo7ueyni