Maxim Buzdalov | DeepAI

DeepAI AI Chat

Featured Co-authors

Benjamin Doerr
91 publications
Carola Doerr
90 publications
Denis Antipov
11 publications
Nguyen Dang
8 publications
Arina Buzdalova
6 publications
Kirill Antonov
4 publications
Anatoly Shalyto
4 publications
Nina Bulanova
3 publications
Anton Bassin
2 publications
Viktor Arkhipov
1 publication
Ilya Yakupov
1 publication

∙ 06/29/2023

Improving Time and Memory Efficiency of Genetic Algorithms by Storing Populations as Minimum Spanning Trees of Patches

In many applications of evolutionary algorithms the computational cost o...

0 Maxim Buzdalov, et al. ∙

∙ 02/23/2023

Using Automated Algorithm Configuration for Parameter Control

Dynamic Algorithm Configuration (DAC) tackles the question of how to aut...

0 Deyao Chen, et al. ∙

∙ 04/14/2021

Lazy Parameter Tuning and Control: Choosing All Parameters Randomly From a Power-Law Distribution

Most evolutionary algorithms have multiple parameters and their values d...

0 Denis Antipov, et al. ∙

∙ 02/23/2021

Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms

With the goal to provide absolute lower bounds for the best possible run...

0 Kirill Antonov, et al. ∙

∙ 02/09/2021

Optimal Static Mutation Strength Distributions for the (1+λ) Evolutionary Algorithm on OneMax

Most evolutionary algorithms have parameters, which allow a great flexib...

0 Maxim Buzdalov, et al. ∙

∙ 06/22/2020

First Steps Towards a Runtime Analysis When Starting With a Good Solution

The mathematical runtime analysis of evolutionary algorithms traditional...

0 Denis Antipov, et al. ∙

∙ 06/20/2020

Optimal Mutation Rates for the (1+λ) EA on OneMax

The OneMax problem, alternatively known as the Hamming distance problem,...

0 Maxim Buzdalov, et al. ∙

∙ 04/20/2020

Fixed-Target Runtime Analysis

Runtime analysis aims at contributing to our understanding of evolutiona...

0 Maxim Buzdalov, et al. ∙

∙ 04/18/2020

The (1+(λ,λ)) Genetic Algorithm for Permutations

The (1+(λ,λ)) genetic algorithm is a bright example of an evolutionary a...

0 Anton Bassin, et al. ∙

∙ 04/14/2020

Fast Mutation in Crossover-based Algorithms

The heavy-tailed mutation operator proposed in Doerr et al. (GECCO 2017)...

0 Denis Antipov, et al. ∙

∙ 04/15/2019

The 1/5-th Rule with Rollbacks: On Self-Adjustment of the Population Size in the (1+(λ,λ)) GA

Self-adjustment of parameters can significantly improve the performance ...

0 Anton Bassin, et al. ∙

∙ 04/09/2019

Black-Box Complexity of the Binary Value Function

The binary value function, or BinVal, has appeared in several studies in...

0 Nina Bulanova, et al. ∙

∙ 04/15/2018

Better Fixed-Arity Unbiased Black-Box Algorithms

In their GECCO'12 paper, Doerr and Doerr proved that the k-ary unbiased ...

0 Nina Bulanova, et al. ∙

∙ 04/14/2018

On Asynchronous Non-Dominated Sorting for Steady-State Multiobjective Evolutionary Algorithms

In parallel and distributed environments, generational evolutionary algo...

0 Ilya Yakupov, et al. ∙

∙ 04/14/2017

Runtime Analysis of the (1+(λ,λ)) Genetic Algorithm on Random Satisfiable 3-CNF Formulas

The (1+(λ,λ)) genetic algorithm, first proposed at GECCO 2013, showed a ...

0 Maxim Buzdalov, et al. ∙

∙ 10/01/2015

An Asynchronous Implementation of the Limited Memory CMA-ES

We present our asynchronous implementation of the LM-CMA-ES algorithm, w...

0 Viktor Arkhipov, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world